!NB.:NO_STABLE_IDS-YET! Expected end Oct-Nov 2025 26.10.2025 01:04 UTC EDAM EDAM http://edamontology.org/ "EDAM relations and concept properties" EDAM_data http://edamontology.org/data_ "EDAM types of data" EDAM_format http://edamontology.org/format_ "EDAM data formats" EDAM_operation http://edamontology.org/operation_ "EDAM operations" EDAM_topic http://edamontology.org/topic_ "EDAM topics" EDAM Bioimaging is an extension to the EDAM ontology (edamontology.org) dedicated to imaging and (bio)image informatics. It has been developed by an open, global community of contributors, including consortia and projects such as NEUBIAS/GloBIAS, COMULIS, ELIXIR, Euro-BioImaging, vEM, QUAREP-LiMi, foundingGIDE, EOSC OSCARS, and more. October 2025: EDAM Bioimaging is in the stage of final refinements towards the first full production version. The production version will include persistent, resolvable identifiers for all concepts; a merged version with the main EDAM; and coverage of microscopy across bio- and other sciences (e.g. materials science and solid-state physics, chemistry, geology, archaeology, cultural heritage), and both clinical and preclinical medical imaging. Further additions and refinements are planned after the production release. Aaron Ponti Alban Gaignard Alexandre Dufour Chong Zhang Daniel Sage David Hörl David Rousseau Dominic Waithe Estibaliz Gómez de Mariscal Fabienne Rössler Florian Levet Gabriella Rustici Ivana Vrhovac Madunić Jean-Baptiste Sibarita Jeremy Pike John Bogovic Joshua Moore Julien Colombelli Kota Miura Lassi Paavolainen Laura Nicolás Sáenz Leandro Scholz Marie-Charlotte Domart María Arrate Muñoz-Barrutia Matthia Karreman NEUBIAS "taggers" and members of NEUBIAS WG4 lead by Perrine Paul-Gilloteaux and WG5 lead by Sébastien Tosi Nataša Sladoje-Matić Ofra Golani Paula Sampaio Perrine Paul-Gilloteaux Petter Ranefall Raf Van de Plas Robert Haase Romain Guiet Sebastian Munck Xavier Heiligenstein Anatole Chessel Hervé Ménager Joakim Lindblad Jon Ison Laure Plantard Leandro Aluisio Scholz Martin Jones Matúš Kalaš Moritz Alexander Kirschmann Moritz Kirschmann Nataša Sladoje An ontology of imaging and related techniques and technologies, image processing and analysis, image data and formats, within bio- and other sciences. application/rdf+xml EDAM (Bio)imaging ontology 1.0alpha bioimaging "EDAM-bioimaging" concept_properties "EDAM concept properties" data "EDAM types of data" edam "EDAM" formats "EDAM data formats" identifiers "EDAM types of identifiers" operations "EDAM operations" relations "EDAM relations" topics "EDAM topics" Matúš Kalaš 1.0alpha_pre-pre-release-20251026T0104Z _Deprecated ID Unique, permanent, and at most one per concept. _Permanent ID Especially if the rdfs:label is long, it is recommended for applications to show abbreviation as the primary display label. Example: MALDI-MS. Just like rdfs:label, edam:abbreviation can be stated at most once per concept and language. To avoid ambiguity, EDAM aims at stating an edam:abbreviation only if: it is unique (or accordingly disambiguated) throughout EDAM; and has at least 4 characters (exceptionally 3 characters), or 2-3 characters plus another word. Other abbreviations in EDAM should be stated only as hasExactSynonym, or as part of other synonyms. Abbreviation 1.13 true Publication reference 'Citation' concept property ('citation' metadata tag) contains a dereferenceable URI, preferrably including a DOI, pointing to a citeable publication of the given data format. Publication concept_properties Citation true Version in which a concept was created. concept_properties Created in true 'Documentation' trailing modifier (qualifier, 'documentation') of 'xref' links of 'Format' concepts. When 'true', the link is pointing to a page with explanation, description, documentation, or specification of the given data format. Specification concept_properties Documentation true 'Example' concept property ('example' metadata tag) lists examples of valid values of types of identifiers (accessions). Applicable to some other types of data, too. concept_properties Separated by bar ('|'). Example true 'File extension' concept property ('file_extension' metadata tag) lists examples of usual file extensions of formats. concept_properties Separated by bar ('|'), without a dot ('.') prefix, preferrably not all capital characters. File extension true 'Hide in subset' concept property ('hide_in_subset' metadata tag) is an experimental (temporary?) property in EDAM Bioimaging that declares a subset in which the given concept may (or should) be hidden from users. concept_properties N.B.: In full mature EDAM, this will be implicit by not including the given concepts in the given subset. N.B.: In generated subsets, these concepts should be omitted, and their children re-rooted (while omitting unneccessary|uninteresting paths to root!!). Hide in subset true 'Media type' trailing modifier (qualifier, 'media_type') of 'xref' links of 'Format' concepts. When 'true', the link is pointing to a page specifying a media type of the given data format. MIME type concept_properties Media type true Version in which a concept was made obsolete. concept_properties Obsolete since true 'Regular expression' concept property ('regex' metadata tag) specifies the allowed values of types of identifiers (accessions). Applicable to some other types of data, too. concept_properties Regular expression 'Related term' concept property ('related_term'; supposedly a synonym modifier in OBO format) states a related term - not necessarily closely semantically related - that users (also non-specialists) may use when searching. concept_properties Related term true 'Repository' trailing modifier (qualifier, 'repository') of 'xref' links of 'Format' concepts. When 'true', the link is pointing to the public source-code repository where the given data format is developed or maintained. Public repository Source-code repository Repository Matúš Kalaš 20250313-1921 can use false false false OBO_REL:is_a 'A has_format B' defines for the subject A, that it has the object B as its data format. edam relations false Subject A can be any concept or entity outside of an ontology (or an ontology concept in a role of an entity being semantically annotated) that is (or is in a role of) 'Data', or an input, output, input or output argument of an 'Operation'. Object B can either be a concept that is a 'Format', or in unexpected cases an entity outside of an ontology that is a 'Format' or is in the role of a 'Format'. In EDAM, 'has_format' is not explicitly defined between EDAM concepts, only the inverse 'is_format_of'. has format "http://purl.obolibrary.org/obo/OBI_0000298" http://www.loa-cnr.it/ontologies/DOLCE-Lite.owl#has-quality" false false false OBO_REL:is_a 'A has_function B' defines for the subject A, that it has the object B as its function. OBO_REL:bearer_of edam relations true Subject A can be any concept or entity outside of an ontology (or an ontology concept in a role of an entity being semantically annotated). Object B can either be a concept that is (or is in a role of) a function, or an entity outside of an ontology that is (or is in a role of) a function specification. In the scope of EDAM, 'has_function' serves only for relating annotated entities outside of EDAM with 'Operation' concepts. has function "http://purl.obolibrary.org/obo/OBI_0000306" http://wsio.org/has_function http://www.loa-cnr.it/ontologies/DOLCE-Lite.owl#has-quality" OBO_REL:bearer_of Is defined anywhere? Not in the 'unknown' version of RO. 'OBO_REL:bearer_of' is narrower in the sense that it only relates ontological categories (concepts) that are an 'independent_continuant' (snap:IndependentContinuant) with ontological categories that are a 'specifically_dependent_continuant' (snap:SpecificallyDependentContinuant), and broader in the sense that it relates with any borne objects not just functions of the subject. true In very unusual cases. false false false OBO_REL:is_a 'A has_identifier B' defines for the subject A, that it has the object B as its identifier. edam relations false Subject A can be any concept or entity outside of an ontology (or an ontology concept in a role of an entity being semantically annotated). Object B can either be a concept that is an 'Identifier', or an entity outside of an ontology that is an 'Identifier' or is in the role of an 'Identifier'. In EDAM, 'has_identifier' is not explicitly defined between EDAM concepts, only the inverse 'is_identifier_of'. has identifier false false false OBO_REL:is_a 'A has_input B' defines for the subject A, that it has the object B as a necessary or actual input or input argument. OBO_REL:has_participant edam relations true Subject A can either be concept that is or has an 'Operation' function, or an entity outside of an ontology (or an ontology concept in a role of an entity being semantically annotated) that has an 'Operation' function or is an 'Operation'. Object B can be any concept or entity. In EDAM, only 'has_input' is explicitly defined between EDAM concepts ('Operation' 'has_input' 'Data'). The inverse, 'is_input_of', is not explicitly defined. has input "http://purl.obolibrary.org/obo/OBI_0000293" http://wsio.org/has_input OBO_REL:has_participant 'OBO_REL:has_participant' is narrower in the sense that it only relates ontological categories (concepts) that are a 'process' (span:Process) with ontological categories that are a 'continuant' (snap:Continuant), and broader in the sense that it relates with any participating objects not just inputs or input arguments of the subject. true In very unusual cases. false false false OBO_REL:is_a 'A has_output B' defines for the subject A, that it has the object B as a necessary or actual output or output argument. OBO_REL:has_participant edam relations true Subject A can either be concept that is or has an 'Operation' function, or an entity outside of an ontology (or an ontology concept in a role of an entity being semantically annotated) that has an 'Operation' function or is an 'Operation'. Object B can be any concept or entity. In EDAM, only 'has_output' is explicitly defined between EDAM concepts ('Operation' 'has_output' 'Data'). The inverse, 'is_output_of', is not explicitly defined. has output "http://purl.obolibrary.org/obo/OBI_0000299" http://wsio.org/has_output OBO_REL:has_participant 'OBO_REL:has_participant' is narrower in the sense that it only relates ontological categories (concepts) that are a 'process' (span:Process) with ontological categories that are a 'continuant' (snap:Continuant), and broader in the sense that it relates with any participating objects not just outputs or output arguments of the subject. It is also not clear whether an output (result) actually participates in the process that generates it. true In very unusual cases. has part false false false OBO_REL:is_a 'A has_topic B' defines for the subject A, that it has the object B as its topic (A is in the scope of a topic B). edam relations true Subject A can be any concept or entity outside of an ontology (or an ontology concept in a role of an entity being semantically annotated). Object B can either be a concept that is a 'Topic', or in unexpected cases an entity outside of an ontology that is a 'Topic' or is in the role of a 'Topic'. In EDAM, only 'has_topic' is explicitly defined between EDAM concepts ('Operation' or 'Data' 'has_topic' 'Topic'). The inverse, 'is_topic_of', is not explicitly defined. has topic "http://purl.obolibrary.org/obo/IAO_0000136" "http://purl.obolibrary.org/obo/OBI_0000298" http://annotation-ontology.googlecode.com/svn/trunk/annotation-core.owl#hasTopic http://www.loa-cnr.it/ontologies/DOLCE-Lite.owl#has-quality true In very unusual cases. false false false OBO_REL:is_a 'A is_format_of B' defines for the subject A, that it is a data format of the object B. OBO_REL:quality_of edam relations false Subject A can either be a concept that is a 'Format', or in unexpected cases an entity outside of an ontology (or an ontology concept in a role of an entity being semantically annotated) that is a 'Format' or is in the role of a 'Format'. Object B can be any concept or entity outside of an ontology that is (or is in a role of) 'Data', or an input, output, input or output argument of an 'Operation'. In EDAM, only 'is_format_of' is explicitly defined between EDAM concepts ('Format' 'is_format_of' 'Data'). The inverse, 'has_format', is not explicitly defined. is format of http://www.loa-cnr.it/ontologies/DOLCE-Lite.owl#inherent-in OBO_REL:quality_of Is defined anywhere? Not in the 'unknown' version of RO. 'OBO_REL:quality_of' might be seen narrower in the sense that it only relates subjects that are a 'quality' (snap:Quality) with objects that are an 'independent_continuant' (snap:IndependentContinuant), and is broader in the sense that it relates any qualities of the object. false false false OBO_REL:is_a 'A is_function_of B' defines for the subject A, that it is a function of the object B. OBO_REL:function_of OBO_REL:inheres_in edam relations true Subject A can either be concept that is (or is in a role of) a function, or an entity outside of an ontology (or an ontology concept in a role of an entity being semantically annotated) that is (or is in a role of) a function specification. Object B can be any concept or entity. Within EDAM itself, 'is_function_of' is not used. is function of http://wsio.org/is_function_of http://www.loa-cnr.it/ontologies/DOLCE-Lite.owl#inherent-in OBO_REL:function_of Is defined anywhere? Not in the 'unknown' version of RO. 'OBO_REL:function_of' only relates subjects that are a 'function' (snap:Function) with objects that are an 'independent_continuant' (snap:IndependentContinuant), so for example no processes. It does not define explicitly that the subject is a function of the object. OBO_REL:inheres_in Is defined anywhere? Not in the 'unknown' version of RO. 'OBO_REL:inheres_in' is narrower in the sense that it only relates ontological categories (concepts) that are a 'specifically_dependent_continuant' (snap:SpecificallyDependentContinuant) with ontological categories that are an 'independent_continuant' (snap:IndependentContinuant), and broader in the sense that it relates any borne subjects not just functions. true In very unusual cases. false false false OBO_REL:is_a 'A is_identifier_of B' defines for the subject A, that it is an identifier of the object B. edam relations false Subject A can either be a concept that is an 'Identifier', or an entity outside of an ontology (or an ontology concept in a role of an entity being semantically annotated) that is an 'Identifier' or is in the role of an 'Identifier'. Object B can be any concept or entity outside of an ontology. In EDAM, only 'is_identifier_of' is explicitly defined between EDAM concepts (only 'Identifier' 'is_identifier_of' 'Data'). The inverse, 'has_identifier', is not explicitly defined. is identifier of false false false OBO_REL:is_a 'A is_input_of B' defines for the subject A, that it as a necessary or actual input or input argument of the object B. OBO_REL:participates_in edam relations true Subject A can be any concept or entity outside of an ontology (or an ontology concept in a role of an entity being semantically annotated). Object B can either be a concept that is or has an 'Operation' function, or an entity outside of an ontology that has an 'Operation' function or is an 'Operation'. In EDAM, 'is_input_of' is not explicitly defined between EDAM concepts, only the inverse 'has_input'. is input of "http://purl.obolibrary.org/obo/OBI_0000295" http://wsio.org/is_input_of OBO_REL:participates_in 'OBO_REL:participates_in' is narrower in the sense that it only relates ontological categories (concepts) that are a 'continuant' (snap:Continuant) with ontological categories that are a 'process' (span:Process), and broader in the sense that it relates any participating subjects not just inputs or input arguments. true In very unusual cases. false false false OBO_REL:is_a 'A is_output_of B' defines for the subject A, that it as a necessary or actual output or output argument of the object B. OBO_REL:participates_in edam relations true Subject A can be any concept or entity outside of an ontology (or an ontology concept in a role of an entity being semantically annotated). Object B can either be a concept that is or has an 'Operation' function, or an entity outside of an ontology that has an 'Operation' function or is an 'Operation'. In EDAM, 'is_output_of' is not explicitly defined between EDAM concepts, only the inverse 'has_output'. is output of "http://purl.obolibrary.org/obo/OBI_0000312" http://wsio.org/is_output_of OBO_REL:participates_in 'OBO_REL:participates_in' is narrower in the sense that it only relates ontological categories (concepts) that are a 'continuant' (snap:Continuant) with ontological categories that are a 'process' (span:Process), and broader in the sense that it relates any participating subjects not just outputs or output arguments. It is also not clear whether an output (result) actually participates in the process that generates it. true In very unusual cases. false false false OBO_REL:is_a 'A is_topic_of B' defines for the subject A, that it is a topic of the object B (a topic A is the scope of B). OBO_REL:quality_of edam relations true Subject A can either be a concept that is a 'Topic', or in unexpected cases an entity outside of an ontology (or an ontology concept in a role of an entity being semantically annotated) that is a 'Topic' or is in the role of a 'Topic'. Object B can be any concept or entity outside of an ontology. In EDAM, 'is_topic_of' is not explicitly defined between EDAM concepts, only the inverse 'has_topic'. is topic of http://www.loa-cnr.it/ontologies/DOLCE-Lite.owl#inherent-in OBO_REL:quality_of Is defined anywhere? Not in the 'unknown' version of RO. 'OBO_REL:quality_of' might be seen narrower in the sense that it only relates subjects that are a 'quality' (snap:Quality) with objects that are an 'independent_continuant' (snap:IndependentContinuant), and is broader in the sense that it relates any qualities of the object. true In very unusual cases. part of Matúš Kalaš 20250313-1914 usable in usable for related beta12orEarlier Information, represented in an information artefact (data record) that is 'understandable' by dedicated computational tools that can use the data as input or produce it as output. Data record Data set Datum navigation Data "http://purl.obolibrary.org/obo/IAO_0000027" "http://purl.obolibrary.org/obo/IAO_0000030" http://purl.org/biotop/biotop.owl#DigitalEntity http://semanticscience.org/resource/SIO_000069 http://semanticscience.org/resource/SIO_000088 http://wsio.org/data_002 http://www.ifomis.org/bfo/1.1/snap#Continuant http://www.onto-med.de/ontologies/gfo.owl#Perpetuant Data record EDAM does not distinguish a data record (a tool-understandable information artefact) from data or datum (its content, the tool-understandable encoding of an information). Data set EDAM does not distinguish the multiplicity of data, such as one data item (datum) versus a collection of data (data set). Datum EDAM does not distinguish the multiplicity of data, such as one data item (datum) versus a collection of data (data set). Mass spectrum Mass spectra bioimaging data edam 1D image Metadata tile tiling A (2D) image is the optical counterpart of an object produced by an optical or an electronic device. A (2D) digital image is a representation of a real (2D) image in a form of a 2D array, or matrix, containing numbers that can be stored and handled by a digital computer. bioimaging data edam For each pixel, the imaging device records a number, or a small set of numbers, that describe some property of this pixel, such as its brightness (the intensity of the light) or its color. Numbers in a matrix are responses from a sensor measured at a set of sampling points, arranged into rows and columns. Digital image is a union of pixels - picture elements - assigned to sampling points. Pixels are typically square regions centered at a sampling point. wikipedia has a poor definition of an image 2D image stack Image stack bioimaging data edam 3D image bioimaging data edam nD image channel rgb bioimaging data edam Colour bioimaging data edam Greyscale Image data Digital image Image set Pixel-based image Raster image Set of images Voxel-based image bioimaging data edam Image bioimaging data edam Image data properties bioimaging data edam Image histogram bioimaging data edam Intensity ROI bioimaging data edam Region of interest bioimaging data edam Time bioimaging data edam Time-lapse data bioimaging data edam Object trajectory bioimaging data edam Volume bioimaging data edam Multi-channel image bioimaging data edam Image radiometric noise characteristics bioimaging data edam Spatial properties bioimaging data edam Temporal properties Image metadata bioimaging data edam Image characteristics Object speed bioimaging data edam Object velocity bioimaging data edam Spatial image resolution bioimaging data edam Spectral properties Time-series image Movie Time-lapse image Video sequence bioimaging data edam Image time series Image bioimaging data edam So far consensus: Primary term Image data, exact synonym Image, meaning image or a set of (related) images (forming e.g. a stack or a time-lapse). No synonyms for stacks and "movies", these should be specialised concepts. Image data bioimaging data edam Region properties bioimaging data edam Radiometric properties bioimaging data edam Spectral image resolution bioimaging data edam Image bit depth bioimaging data edam Image radiometric noise bioimaging data edam Region texture bioimaging data edam Object shape Object data Object feature Object measurement bioimaging data edam Object characteristics Image formation characteristics Image sensor characteristics Lens distortion characteristics Instrument distortion characteristics IRF Instrument response function OTF Optical transfer function PSF Point spread function Spatial coordinates Geographical datacube Spatio-temporal datacube Coverage data Datacube Multi-dimensional array Multi-dimensional scalar data Data cube Куб даних データキューブ Instrument parameters and characteristics Ion image is an array of intensity values (abundance of the given ionised molecule type) for each pixel/voxel in an image. An ion image is understood as intensities for one ion (one type of ionised molecule). In practice, hundreds to thousands of molecules are part of a mass spectroscopy imaging data set. The underlying image is usually 2D (plus the intensities). Ion image Ion image labelling? Ion image annotation Mass spectrometry imaging data Mass spectrometry imaging data set is a data cube (typically 4D), consisting of a list of ion images (intensities in all/some(?) positions for 1 molecule type), and a list of mass spectra (intensities of all molecule types for 1 position). So ion image(s) and mass spectra are both part(s) of an MSI data set. Data model File format bioimaging edam formats navigation Work comment: Xavier Heiligenstein 20th March 2019 I would add: dm3, md4, dv, zvi, mrc, st sampaio 4th February 2019 Add pre-clinical and medica specific formats e.g. DICOM Natasa Sladoje 4th February 2019 Some more https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3948928/ Format Data model A defined data format has its implicit or explicit data model, and EDAM does not distinguish the two. Some data models however do not have any standard way of serialisation into an exchange format, and those are thus not considered formats in EDAM. (Remark: even broader - or closely related - term to 'Data model' would be an 'Information model'.) File format File format denotes only formats of a computer file, but the same formats apply also to data blobs or exchanged messages. bioimaging edam formats Binary format Matúš Kalaš 2025-08-15T20:55:39.352613Z imzML is a conglomerate format consisting of 2 files: .idb (http://edamontology.org/format_3839) and imzML metadata file (.imzML, http://edamontology.org/format_3682). imzML .avi bioimaging edam formats avi bioimaging edam formats csv .dat bioimaging edam formats dat h5 bioimaging edam formats hdf5 .hdr bioimaging edam formats hdr .img bioimaging edam formats img .ims bioimaging edam formats ims bioimaging edam formats ism .jpg bioimaging edam formats jpg bioimaging edam formats mpeg .raw bioimaging edam formats raw .scn bioimaging edam formats scn .sm2 bioimaging edam formats sm2 .sm3 bioimaging edam formats sm3 .stk bioimaging edam formats stk bioimaging edam formats tif .tiff bioimaging edam formats tiff .txt bioimaging edam formats txt .vsi bioimaging edam formats vsi .xml bioimaging edam formats xml beta12orEarlier Function A function that processes a set of inputs and results in a set of outputs, or associates arguments (inputs) with values (outputs). Computational method Computational operation Computational procedure Computational subroutine Function (programming) Lambda abstraction Mathematical function Mathematical operation Computational tool Process sumo:Function edam navigation Special cases are: a) An operation that consumes no input (has no input arguments). Such operation is either a constant function, or an operation depending only on the underlying state. b) An operation that may modify the underlying state but has no output. c) The singular-case operation with no input or output, that still may modify the underlying state. Operation http://onto.eva.mpg.de/ontologies/gfo-bio.owl#Method http://purl.org/biotop/biotop.owl#Function http://semanticscience.org/resource/SIO_000017 http://semanticscience.org/resource/SIO_000649 http://wsio.org/operation_001 http://www.ebi.ac.uk/swo/SWO_0000003 http://www.ifomis.org/bfo/1.1/snap#Continuant http://www.ifomis.org/bfo/1.1/snap#Function http://www.ifomis.org/bfo/1.1/snap#Quality http://www.ifomis.org/bfo/1.1/span#Process http://www.loa-cnr.it/ontologies/DOLCE-Lite.owl#process http://www.loa-cnr.it/ontologies/DOLCE-Lite.owl#quality http://www.onto-med.de/ontologies/gfo.owl#Function http://www.onto-med.de/ontologies/gfo.owl#Perpetuant http://www.onto-med.de/ontologies/gfo.owl#Process Function Operation is a function that is computational. It typically has input(s) and output(s), which are always data. Computational tool Computational tool provides one or more operations. Process Process can have a function (as its quality/attribute), and can also perform an operation with inputs and outputs. bioimaging? edam operations Annotation bioimaging? Plotting edam operations Re-occurs among biii.info tags (visualisation, rendering, viewer, classification, ...) Visualisation bioimaging edam operations Data handling bioimaging edam operations Todo: Terms Prediction (https://en.wikipedia.org/wiki/Prediction#Statistics), Forecast, Statistical inference, (Inference|Induction), Inferential statistics, Regression analysis, Hypothesis testing, ... And Regression & Regression analysis versus Training/Parameter optimisation Work comment: Cleared up relation between Classification, Clustering, and Prediction and recognition (also in main EDAM). Now Classification, Clustering, Regression (which needs more terms & related). Recognition only Pattern recognition (maybe even as topic equal to ML). Regression bioimaging edam operations Existence of this term is due to "big" EDAM, is hidden in bioimaging Alignment construction bioimaging Analysis is the process of decomposing a complex topic or substance into smaller parts in order to improve understanding of it. edam operations Analysis bioimaging? edam operations Re-occurs among biii.info tags (visualisation, rendering, viewer, classification, ...) ToDo: Clear up relation between Classification, Clustering, and Prediction and recognition (also in main EDAM) Classification bioimaging edam operations Editing bioimaging Data synthesis edam operations Data generation bioimaging edam operations Conversion bioimaging edam operations Visualisation vs Plotting vs Image generation. Should these be merged? Which of these should be the top concept, and which sub-concepts, and which narrow synonyms? Plotting Image analysis is a process of extraction of meaningful quantitative or qualitative information from (digital) images, by means of digital image processing techniques, typically using computers. General image analysis bioimaging edam operations Image analysis Image annotation is the process of defining metadata to a digital image, e.g. defining regions, marking points, creating textual descriptions, attaching tags to image contents. Can be manual or automatic. bioimaging edam operations Image annotation Data filtering 'Active contours' is an energy-minimizing deformable parametric contour, that is typically used to segment image regions enclosed by edges. Active contour model Active contour models Snakes bioimaging edam operations Active contours Adaptative thresholding Dynamic thresholding Local thresholding bioimaging edam operations Adaptive thresholding bioimaging edam operations Anaglyph bioimaging edam operations Object counting bioimaging edam operations Cell segmentation bioimaging edam operations Cell tracking Closing is a morphological operation comprising an erosion followed by a dilation, that is typically used to remove small isolated holes from an image. bioimaging edam operations Closing Dilation is a morphological operation which expands the shapes contained in the input image based on analysis of how (a centre of) a given structuring element hits, or misses the shape. Dilatation bioimaging edam operations Dilation Distance transform (distance map or distance field) of a (binary) image, w.r.t. an object in the image, transforms the input image into a representation (another image) so that each pixel is assigned its distance to the (closest) object pixel. Signed distance transform assigns, to each pixel, its distance to the object boundary; background pixels are assigned positive distance values, whereas foreground pixels are assigned negative distance values. bioimaging edam operations Distance transform Matching filter Steerable filter Edge enhancement bioimaging edam operations Relation with Edge detection... Feature enhancement Erosion is a morphological operation used to analyse how a (simple) pre-defined probe (called structuring element) fits or misses the shapes in the image. Grey scale erosion computed in an image point is the minimum of the intensities of the points in its neighborhood, where the neighborhood is defined by the structuring element. bioimaging edam operations Erosion Feature detection Image labeling SIFT SURF scale-invariant feature transform bioimaging edam operations Object feature extraction Geometrical transformation bioimaging edam operations Geometric transformation bioimaging edam operations Homogeneity extraction Background subtraction Flat field correction bioimaging edam operations Illumination correction Image clustering An annotation is a metadatum (e.g. a post, explanation, markup) attached to location or other data bioimaging edam operations Image classification Object-based co-localisation analysis Object-based colocalization analysis bioimaging edam operations Object-based colocalisation analysis bioimaging edam operations Image deconvolution Image restoration bioimaging edam operations Image enhancement is a term used to refer to an operation that increases the quality of the image, being historically more used in the context of contrast enhancement (which improves visualization for the human eye). However, image enhancement is also a very general term that refers to operations that enhance features interest in the image. An image enhancement operation moves further away from the "reality", as opposed to Image reconstruction that moves closer to the "reality". Image enhancement Image transformation Image filtering Image post-processing Image postprocessing Image pre-processing Image preprocessing Image manipulation bioimaging edam operations Image processing Image restoration bioimaging edam operations Image enhancement moves further away from the "reality", as opposed to Image reconstruction that moves closer to the "reality". Image reconstruction Image overlay Image registration is the process of aligning, by applying geometric transformation, two or more misaligned images. Image alignment bioimaging edam operations Registration is necessary in order to be able to compare or integrate the data obtained from different sensors/imaging modalities, at different times, from different view points, etc. Registration can be based on correspondence established between the landmarks or feature points. Alternatively, some similarity/distance metric is established between the image intensity maps to navigate the registration process. Image registration bioimaging edam operations Image segmentation is (one of) the (few) concept(s) on the border between Image (pre)processing (Image->Image) and Image analysis (Image->Data). Image segmentation Gaussian blurring Gaussian filtering Gaussian smoothing Blurring Smoothing bioimaging edam operations Image smoothing Tile Tiling Mosaic bioimaging edam operations Image stitching Thresholding Clustering-based image thresholding bioimaging edam operations Image thresholding Tracking Trajectory extraction bioimaging edam operations Object tracking Rendering Lookup table bioimaging edam operations Visualisation vs Plotting vs Image generation. Should these be merged? Which of these should be the top concept, and which sub-concepts, and which narrow synonyms? Image visualisation bioimaging edam operations Interactive segmentation Image resampling bioimaging edam operations Linear transformation bioimaging edam operations Montage Mathematical morphology Mathematical morphology is a theory and technique for the analysis and processing of geometrical structures, based on set theory, lattice theory, topology, and random functions. MM is most commonly applied to digital images, but it can be employed as well on graphs, surface meshes, solids, and many other spatial structures. Topological and geometrical continuous-space concepts such as size, shape, convexity, connectivity, and geodesic distance, were introduced by MM on both continuous and discrete spaces. MM is also the foundation of morphological image processing, which consists of a set of operators that transform images according to the above characterizations. The basic morphological operators are erosion, dilation, opening and closing. Morphological image processing bioimaging edam operations Morphological operation Image feature extraction bioimaging edam operations Image feature detection Opening is a morphological operation comprising a dilation followed by an erosion, that is typically used to remove small isolated objects from an image. bioimaging edam operations Opening The process of estimating apparent (relative) motion in an image or scene, typically represented as vector field. bioimaging edam operations Optical flow is the distribution of the apparent velocities of objects in an image. It is used in object tracking systems, to characterize and quantify the motion of objects in a video stream. Optical flow analysis bioimaging edam operations Overlay bioimaging edam operations Particle tracking Pixel labeling Voxel classification Semantic image segmentation Semantic segmentation bioimaging Pixel classification Maximum projection Minimum projection Maximum intensity projection Mean projection bioimaging edam operations Image projection bioimaging edam operations Rotation Shape feature extraction Area bioimaging edam operations Shape features extraction Skeletonisation is a process for generating fogroundreducing foreground regions in a binary image to a skeletal remnant that largely preserves the extent and connectivity of the original region while throwing away most of the original foreground pixels Skeletonisation is a process of reducing a foreground region in a (binary) image into its simplified, topologically equivalent representation - skeleton. The new representation contains highly reduced number of foreground pixels, while largely preserving the extent and connectivity of the original region. Medial axis transform bioimaging edam operations Skeletonisation Seed point detection bioimaging edam operations Spot detection Texture feature extraction Inverse Difference Moment bioimaging edam operations Texture extraction bioimaging edam operations Volume rendering bioimaging edam operations Warping Watershed transformation Watershed-based segmentation bioimaging edam operations Needs a comment about the relation between the Watershed and Region growing. Watershed is the term that commonly refers to a mathematical morphology operation that treats a grayscale image as a topographic map and segments the image. The segmentation is performed by a succesive 'flooding' operation from minima in the image starting from different points and separates the image in different catchment basins. Watershed segmentation Tomography reconstruction Filtered back projection bioimaging edam operations Tomographic reconstruction Lens distortion correction bioimaging edam operations Geometric distortion correction Image correction is the removal of aberrations originating from the imaging instrument, lighting, or sample. Instrument aberration correction Image pre-processing Image preprocessing bioimaging edam operations Image correction Color deconvolution bioimaging edam operations Spectral unmixing Orthographic projection bioimaging edam operations Affine transformation Single molecule localization PAINT image reconstruction PALM image reconstruction SMLM image reconstruction STORM image reconstruction Single-molecule localisation microscopy image reconstruction Single-molecule localization microscopy image reconstruction bioimaging edam operations Single molecule localisation bioimaging edam operations Structured illumination reconstruction Object registration Shape-based registration bioimaging edam operations Feature-based registration Image simulation Image synthesis Simulated image generation bioimaging edam operations Synthetic image generation Neuron reconstruction Tubular structure extraction Biofilament tracing Curvilinear structure detection Curvilinear structure reconstruction bioimaging edam operations Filament tracing operations are image analysis operations in which there is an image of a filamentous structure (it may be a tree-like structure, a filament network or a agglomeration of single 'stick-like' filaments) as input and outputs data that represent the filament, most commonly a skeleton representation of the filaments and their diameters or surfaces. Filament tracing Rigid image registration bioimaging edam operations Parametric (global) registration restricted to rigid transformations (translation and rotation). Rigid registration Isolated object detection Object localisation Object localization Particle detection bioimaging edam operations Object detection bioimaging edam operations Selective plane illumination microscopy reconstruction Scratch assay Scratch assay analysis Wound healing analysis Wound-healing assay bioimaging edam operations Collective object tracking FFT Frequency domain analysis is a process that quantifies the various amounts (e.g. amplitudes, powers, intensities, or phases), versus frequency. It requires decomposition a complex signal into a sum of many individual frequency components. Analysis in the frequency domain Fast Fourier transform Wavelet transform bioimaging edam operations Analysis in the frequency domain is applicable within signal analysis in general, including image analysis. Frequency domain analysis (or spectral density estimation), is the process of decomposing a complex signal into simpler parts. Many physical processes are best described as a sum of many individual frequency components. Any process that quantifies the various amounts (e.g. amplitudes, powers, intensities, or phases), versus frequency can be called spectrum analysis. The Fourier transform of a function produces its frequency spectrum by decomposing the function into its sine and cosine components. Whereas the standard Fourier transform is only localized in frequency, wavelets are localized in both time and frequency. Wavelets are handcrafted to correlate with particular frequencies in a signal; a set of wavelets is usually used for a complete analysis. Frequency-domain analysis bioimaging edam operations Drift correction Elastic registration bioimaging edam operations Deformable registration bioimaging edam operations multiplicative Detector gain correction Image synthesis bioimaging edam operations Image generation bioimaging edam operations Pattern recognition aims at identifying regularities in data and includes classification, clustering, anomaly detection, density estimation, etc. This can be done in both supervised and unsupervised manner. Todo: Consider Pattern recognition as some form of synonym of topic ML instead(?) Pattern recognition Seed point selection Reference point assignment Fiducial placement bioimaging edam operations Labelling? Not allowed to stand alone, needs additional modifiers as means various things. Maybe not that relevant here. Anywhere else? Landmark assignment https://en.wikipedia.org/wiki/Landmark_point https://en.wikipedia.org/wiki/Fiducial_marker https://en.wikipedia.org/wiki/Region_growing Camera bias correction bioimaging edam operations Additive Detector bias correction Channel shift correction bioimaging edam operations Chromatic aberration correction bioimaging edam operations Isolated object tracking Noise reduction bioimaging edam operations Image denoising Affine image registration bioimaging edam operations Parametric (global) registration restricted to affine transforms (allowing translation, rotation, scaling, shear, reflection and their compositions). Affine registration bioimaging edam operations Image crop Isolated object classification Semantic object classification bioimaging operations Object classification Clustering (or cluster analysis) is a process of grouping a set of data points (objects) in such a way that objects in the same group (forming a cluster) are, in some sense, more similar to each other than to those in other groups (clusters). Clustering is sometimes referred to as unsupervised classification. Cluster analysis bioimaging edam operations Clustering Co-localisation analysis Co-localization analysis Colocalization analysis bioimaging edam operations Colocalisation analysis Linear shift invariant image filtering bioimaging edam operations Image convolution bioimaging edam operations Image validation Optimization or refinement bioimaging edam operations Optimisation or refinement Model optimisation Model training Parameter optimization bioimaging edam operations ToDo: Add wrt ML/statistical (brainstorming Joakim, Martin, Daniel Sage, Estibaliz...): Training/Learning, Model fitting, (Statistical/ML) Model optimisation/fine-tuning, Hyperparameter optimisation/tuning, Transfer learning, Supervised/Reinforcement/Unsupervised/Semi-supervised, (Regression, Regression analysis?), Energy minimisation, Empirical risk minimisation, Likelihood maximisation, Expectation maximisation, Data augmentation (needs a less ambiguous label), Parameter optimisation Manders coefficient Pixel-based co-localisation analysis Pixel-based colocalization analysis Voxel-based colocalisation analysis bioimaging edam operations Pixel-based colocalisation analysis Displacement analysis Motility analysis bioimaging edam operations Trajectory analysis bioimaging edam operations Validation Scratch assay Wound-healing assay Wound-healing analysis Operation Contrast enhancement Relation with Feature enhancement Edge detection ToDo: add a few more but not too many specialised concepts under here. Model-based segmentation Region-based segmentation Operations bioimaging edam Needs a comment about the relation between the Watershed and Region growing. Region growing Cut plane rendering Slice viewing Slice rendering Surface rendering Hat transform Top-hat transform is a morphological operation computed by subtracting the opened image from the original input image. It is used to extract small elements and details from given images. White top-hat transform Black top-hat transform Bottom-hat transform The bottom-hat transform: the residual of a closing compared to the original image. Top-hat transform Cell lineage extraction Instance segmentation Connected-component analysis FFT Transformation into frequency domain Fast Fourier transform Wavelet transform bioimaging edam operations Frequency domain analysis (or spectral density estimation), is the process of decomposing a complex signal into simpler parts. Many physical processes are best described as a sum of many individual frequency components. Any process that quantifies the various amounts (e.g. amplitudes, powers, intensities, or phases), versus frequency can be called spectrum analysis. The Fourier transform of a function produces its frequency spectrum by decomposing the function into its sine and cosine components. Whereas the standard Fourier transform is only localized in frequency, wavelets are localized in both time and frequency. Wavelets are handcrafted to correlate with particular frequencies in a signal; a set of wavelets is usually used for a complete analysis. Transformation into frequency domain is applicable within signal processing in general, not only within image processing. Frequency-domain transformation Image fusion is the process of gathering all the important information from multiple images, and their inclusion into fewer images, usually a single one. Image fusion Area-based registration Intensity-based registration Jaccard index Sørensen-Dice coefficient Intersection analysis Overlap quantification Overlap analysis Ridge detection Super-pixel extraction Super-voxel extraction Supervoxel extraction Superpixel extraction Velocity extraction Fuzzy c-means clustering k-means clustering Centroid-based clustering Connectivity-based clustering Hierarchical clustering Synthetically increasing the multiplicity and diversity of data available without collecting new data. Data augmentation relies on a priori knowledge (e.g. of system invariants or the noise structure of the data) to generate more data, typically for training learning models. Common data augmentation techniques include corruption by artificial noise, cropping, padding, rotation, and flipping. Data augmentation Dense image annotation DBSCAN Density-based clustering Gaussian mixture model (GMM) Distribution-based clustering Image-to-image translation is a class of image processing techniques where the goal is to learn the mapping between an input image and an output image. It can be applied to a wide range of applications, such as collection style transfer, imaging modality transfer, object transfiguration, season transfer and photo enhancement. Neural style transfer Style transfer Image-to-image translation Machine learning-based data generation Manual segmentation Semi-automatic segmentation Sparse image annotation Ion and optical/other image co-registration Ion image filtering (by masses) Ion image filtering (by pixels/voxels/ROIs) ROIs selection Selection of regions of interest ROI selection Selection Tissue imaging MCFoell 2025-01-17T08:41:13.358294Z Ion image visualisation is generating a spatial heatmap for one or multiple m/z feature(s) of mass spectrometry imaging data. Ion image visualisation MCFoell 2025-01-17T08:44:37.897393Z Ion image normalisation is normalising mass spectra intensities of mass spectrometry imaging data. Ion image normalisation MCFoell 2025-01-17T08:55:29.694009Z Ion image segmentation is the spatial segmentation of a single (univariate) or multiple (multivariate) m/z feature(s) in mass spectrometry imaging data. Typically performed in an unsupervised way and for visual analysis and comparison with histology images. Ion image segmentation MCFoell 2025-01-17T08:57:23.072682Z Univariate ion image segmentation is the spatial segmentation of a single (univariate) m/z feature in mass spectrometry imaging data. Univariate ion image segmentation MCFoell 2025-01-17T08:58:23.552733Z Multivariate ion image segmentation is the spatial segmentation of multiple (multivariate) m/z features in mass spectrometry imaging data. Multivariate ion image segmentation MCFoell 2025-01-17T09:05:25.884957Z Ion image pixel classification is classifying mass spectra (i.e. pixels) of mass spectrometry imaging data. Ion image pixel classification MCFoell 2025-01-17T09:11:03.686925Z Ion image classification is classifying entire samples (typically tissues) measured by mass spectrometry imaging. Ion image classification MCFoell 2025-01-17T09:15:33.096126Z Ion image colocalisation analysis aims to find m/z features with similar spatial distributions (=colocalisation) by correlating the intensity of m/z features across all the ion images collected for a mass spectrometry imaging dataset. Typically uses a reference m/z feature or a defined region (e.g. segment) and searches for m/z features with similar spatial distribution (=colocalisation). Ion image colocalisation analysis beta12orEarlier A category denoting a rather broad domain or field of interest, of study, application, work, data, or technology. Topics have no clearly defined borders between each other. sumo:FieldOfStudy navigation Topic http://bioontology.org/ontologies/ResearchArea.owl#Area_of_Research http://onto.eva.mpg.de/ontologies/gfo-bio.owl#Method http://purl.org/biotop/biotop.owl#Quality http://www.ifomis.org/bfo/1.1/snap#Continuant http://www.ifomis.org/bfo/1.1/snap#Quality http://www.loa-cnr.it/ontologies/DOLCE-Lite.owl#quality http://www.onto-med.de/ontologies/gfo.owl#Category http://www.onto-med.de/ontologies/gfo.owl#Perpetuant Mass spectrometry Natural language processing NMR spectroscopy beta12orEarlier HOESY Heteronuclear Overhauser Effect Spectroscopy NOESY Nuclear Overhauser Effect Spectroscopy ROESY Rotational Frame Nuclear Overhauser Effect Spectroscopy Magnetic resonance spectroscopy (MRS) bioimaging edam topics Nuclear magnetic resonance spectroscopy beta12orEarlier Electron microscope Any form of microscopy that uses a beam of accelerated electrons to image a sample. Electron microscopes can image at higher resolution than light microscopy due to the smaller de Broglie wavelength of the electrons. EM bioimaging edam topics Electron microscopy Cell biology Cellular biology Cytology beta12orEarlier XRD, DRX X-ray diffractometry 1.4 bioimaging edam topics Imaging 1.4 The use of imaging techniques to understand biology. Biological imaging Bioscientific imaging bioimaging edam topics Bioimaging 1.4 Light microscope Optical microscope Light microscopy regroups all techniques in microscopy using light to illuminate and produce an image of a sample. Optical microscopy bioimaging edam topics a list of technique to add is to be found here: https://docs.google.com/document/d/1amTDpRLmoER8pA4IlGMChFfTHzHmMCFcaqUA1xQBd3k/edit Light microscopy 1.7 Technique using magnetic fields and radio waves to generate images of organs. MRI bioimaging edam topics Magnetic resonance imaging 1.7 Elastic neutron scattering Neutron diffraction 1.7 Imaging in sections (sectioning), through the use of a wave-generating device (tomograph) that generates an image (a tomogram). bioimaging edam topics Tomography ML Statistical learning Data mining bioimaging edam topics Machine learning 1.24 Cytometry is the measurement of the characteristics of cells. Cytometry 1.26 Electroencephalography EEG bioimaging edam topics The monitoring method for measuring electrical activity in the brain. 1.26 Electrocardiography EKG ECG bioimaging edam topics The monitoring method for measuring electrical activity in the heart. Tissue image informatics Tissue image analysis bioimaging edam topics Digital histology Techniques in microscopy based on the use of fluorescent molecules that emit light upon excitation. bioimaging edam topics Fluorescence microscopy HCA High-content imaging High-content screening (HCS) bioimaging edam topics In simple terms, high-content screening (HCS) is the combination of high-throughput screening (HTS) applied to high-content analysis (HCA). High-content analysis Fluorescence microscopy technique where the illumination of the sample is performed along a plane and where the detection arm collects the emitted fluorescence from this plane. Light sheet fluorescence microscopy (LSFM) Light-sheet microscopy Digitally scanned laser light-sheet microscopy (DSLM) Lattice light-sheet microscopy (LLS) Objective-coupled planar illumination (OCPI) microscopy Oblique plane microscopy (OPM) Orthogonal-plane fluorescence optical sectioning (OPFOS) Selective plane illumination microscopy (SPIM) Swept confocally-aligned planar excitation microscopy (SCAPE) Thin sheet laser imaging microscopy (TSLIM) epi-illumination SPIM (eSPIM) mesoscale selective plane illumination microscopy (mesoSPIM) Bessel beam lightsheet microscopy CLARITY Optimized Light Sheet Microscopy (COLM) Clarity-optimised light-sheet microscopy Dual-view inverted SPIM (diSPIM) Lattice light-sheet microscopy (LLSM) Multidirectional SPIM Multiview selective plane illumination microscopy (MuViSPIM) SPED Single-objective selective plane illumination microscopy (soSPIM) Spherical aberrations-assisted extended depth-of-field light-sheet microscopy (SPED) inverted SPIM (iSPIM) mSPIM optical projection tomography in light sheet microscopy (OPTiSPIM) bioimaging edam topics Light sheet microscopy The use of microscopes to enlarge objects that are too small to be seen with the naked eye. Slide scanner bioimaging edam topics Microscopy Neuron image informatics Connectomics bioimaging edam topics Neuron image analysis bioimaging edam topics Statistics and probability Group of microscopy techniques that circumvent the diffration limit and therefore allow for a greater spatial resolution limit. SR microscopy (SRM) Sub-diffraction microscopy High-resolution microscopy Optical nanoscopy Super-resolution fluorescence microscopy bioimaging edam topics There are rare exceptions of super-resolution microscopy, such as scanning near-field optical microscopy (SNOM), that do not necessarily rely on fluorescence. Super-resolution microscopy Widefield microscopy is a fluorescence microscopy technique in which the entire sample is illuminated concurrently, and the emission is either visualised by an observer, or captured by a camera. Widefield fluorescence microscopy Epi-fluorescence microscopy Epifluorescence microscopy bioimaging edam topics Widefield microscopy Cryo-fixation bioimaging edam topics Cryofixation Transmission electron microscope In TEM, a beam of electrons is transmitted through an ultrathin sample (typically less than 100 nm thick). Transmitted electrons interact with the sample and are focused onto an imaging device such as a fluorescent screen, photographic film or camera. TEM bioimaging edam topics Transmission electron microscopy Microscopy techniques relying on the point by point imaging of the entire sample. This is typically performed with point illumination of the sample. 4Pi microscopy Controlled light exposure microscopy bioimaging edam topics Point-scanning microscopy Imaging of tissues fixed or kept in physiological but artificial conditions. bioimaging edam topics In-vitro imaging Contrast enhancing technique that relies on the exclusion from the image of light not diffracted by the sample. bioimaging edam topics Dark-field microscopy CLEM Correlative light and electron microscopy is the combination of light microscopy (typically fluorescence microscopy) and electron microscopy of the same sample. Correlative light-electron microscopy Integrated light and electron microscopy (ILEM) Integrated light-electron microscopy Volume correlative light and electron microscopy (Volume CLEM) bioimaging edam topics Correlative light and electron microscopy imaging in the living body of a plant or an animal bioimaging edam topics In-vivo imaging Microscopy technique taking advantage of the properties of birefringent samples illuminated polarized light and observed through a second polariser perpendicular to the first. bioimaging edam topics Polarised light microscopy Polarized light microscopy SMLM SMLM is based on a temporal separation of the emission of fluorescent molecules, allowing a fitting and precise localisation of these molecules. Direct stochastic optical reconstruction microscopy (dSTORM) Fluorescence photoactivation localisation microscopy (fPALM) Ground state depletion individual molecule return (GSDIM) Photoactivated localisation microscopy (PALM) Stochastic optical reconstruction microscopy (STORM) bioimaging edam topics Single molecule localisation microscopy Single molecule localization microscopy 3D reconstruction Morphological reconstruction bioimaging edam topics In-silico reconstruction Optical sectioning Confocal microscopy is fluorescence microscopy in which a pinhole rejects light from out-of-focus planes, allowing an increase in contrast and spatial resolution, mostly axially. Confocal fluorescence microscopy bioimaging edam topics LaureP Matúš Kalaš Confocal microscopy is restricted to objects which are in the same focal plane. Confocal microscopy Process of tilting a sample and collecting images formed at different angles in an electron beam in order to give enhanced 3D information about the sample. Electron Microscopy Array Tomography bioimaging edam topics Electron tomography Techniques in microscopy in which the sample is placed between the illumination source and the observer or recording device. Widefield transmission light microscopy bioimaging edam topics Transmission light microscopy CPD Supercritical drying Supercritical-point drying bioimaging edam topics Critical-point drying Photoacoustic imaging PAT bioimaging edam topics Photoacoustic tomography FIB-SEM Type of scanning electron microscopes performing cycles of ablation of the surface of the sample with an ion beam followed by imaging with an electron beam, therefore allowing the acquisition of 3-dimensional data. FIB SEM FIB/SEM FIBSEM bioimaging edam topics Focused ion beam scanning electron microscopy bioimaging edam topics Ex-vivo imaging Bioimage analysis bioimaging edam topics Bioimage informatics <_permanent_id rdf:resource="http://edamontology.org/topic_3954"/> A diagnostic imaging technique based on the application of ultrasound. Echography Standardized echography Ultrasound imaging Diagnostic sonography Medical ultrasound Standard echography microUS bioimaging edam topics Ultrasonography Fluorescence microscopy technique in which the fluorescent molecule is excited by multiple photons of a wavelength longer than the emission of the fluorescent molecule. Three-photon excitation microscopy (3PEM) Two-photon excitation microscopy (TPEM, 2PEM) bioimaging edam topics Multi-photon microscopy is not confocal in the narrow sense, as it is not using rejection of out-of-focus light (by a pinhole). Multi-photon microscopy Scanning electron microscopy performed on aqueous samples preserved by freezing in liquid nitrogen. Cryo-scanning electron microscopy CryoSEM Cryogenic scanning electron microscopy bioimaging edam topics Scanning electron cryomicroscopy Imaging of biological tissues preserved by chemicals or temperature. bioimaging edam topics Fixed sample imaging Scanning electron microscope In scanning electron microscopy, a focused beam of electrons is raster scanned over the surface of the sample. The image is typically formed by detecting secondary electrons or backscattered electrons. SEM bioimaging edam topics Scanning electron microscopy Spectroscopy refers to the study of how radiated energy and matter interact. The energy is absorbed by the matter, creating an excited state. The interaction creates some form of electromagnetic waves (EM), often in the form of visible light, such as sparks. Spectrometry deals with the measurement of a specific spectrum; essentially the application of spectroscopy so that there are quantifiable results that can then be assessed. Spectrometry bioimaging edam topics Spectroscopy SPECT bioimaging edam topics Single-photon emission computed tomography Array detector microscopy Array-based detection microscopy Area-capturing microscopy Array based detection Camera based microscopy Controlled light exposure microscopy (CLEM) bioimaging edam topics Array detection microscopy An ultramicrotome present inside the SEM allow for serial sectioning of the sample between acquisitions therefore allowing for the generation of 3-dimensional data. SBEM SBF SEM SBFSEM 3View® bioimaging edam topics [3View®] It is not in scope of EDAM to list and model products and vendors, with exceptions of those that are crucial keywords for end users to search for. Todo: add this into general EDAM guidelines. Serial block-face scanning electron microscopy SIM A patterned illumination interferes with the sample and creates moire fringes which are further processed by an algorithm to increase spatial resolution. Instant linear structured Illumination Microscopy Multifocal structured illumination microscopy (MSIM) Saturated structured illumination microscopy (SSIM) iSIM bioimaging edam topics Structured illumination microscopy includes also techniques that do not rely on fluorescence. Structured illumination microscopy Cryo-transmission electron microscopy CryoTEM Cryogenic transmission electron microscopy Cryo-electron tomography CryoET CET bioimaging edam topics Electron cryotomography Microscopy technique relying on the direct observation of samples with light transmitted through them. bioimaging edam topics Bright-field microscopy Computerised tomography Computerized tomography PET microPET bioimaging edam topics Positron emission tomography Recording of native light emission by organism expressing a light emitting molecule. BLI bioimaging edam topics Bioluminescence imaging Dynamic imaging imaging of samples in conditions that keeps them alive, allowing the study of dynamic changes. bioimaging edam topics Live sample imaging STED STED-4Pi An increase in spatial resolution is obtained thanks to stimulated emission properties of fluorophores illuminated simultaneously by two lasers. Reversible saturable optical linear fluorescence transitions microscopy (RESOLFT) gated-STED bioimaging edam topics Stimulated emission depletion microscopy bioimaging edam topics Plunge freezing DIC microscopy Contrast enhancing microscopy technique based on interferences between rays that travel different distances through a sample. Nomarski interferential contrast (NIC) Nomarski microscopy bioimaging edam topics Differential interference contrast microscopy Imaging of a thin specimen by a focused electron beam which is scanned over the sample. STEM bioimaging edam topics Scanning transmission electron microscopy Freeze etching Freeze-etch Freeze-fracture bioimaging edam topics Freeze fracturing bioimaging edam topics Sample preparation bioimaging edam topics High-pressure freezing Phase contrast microscopy is based on the conversion of sample-induced phase shift of light into contrast in an image. Phase imaging Quantitative phase-contrast imaging bioimaging edam topics Phase-contrast microscopy bioimaging edam topics Data sharing CAT scan CT CT scan Computerised axial tomography HRCT High-resolution CT High-resolution micro-CT X-ray computed tomography High-resolution X-ray tomography X-ray tomography bioimaging edam topics CT is usually understood as X-ray CT (https://en.wikipedia.org/wiki/X-ray_computed_tomography redirecting to https://en.wikipedia.org/wiki/CT_scan). On the other hand, Optical tomography can also be CT, see concept Optical projection tomography with its synonyms. Work comment: Radical but perhaps a good consideration is to move CT as a narrow synonym of Tomography. Computed tomography Photobleaching microscopy with non-linear processing PiMP Super-resolution optical fluctuation imaging (SOFI) Super-resolution radial fluctuations (SRRF) bioimaging edam topics Fluctuation-based microscopy FCS FCS measures fluctuations of fluorescence in a volume, providing after analysis physical parameters of the sample such as diffusion coefficient or concentration. Fluorescence Lifetime Correlation Microscopy (FLCS) Fluorescence cross-correlation spectroscopy (FCCS) bioimaging edam topics Fluorescence correlation spectroscopy FLIM Fluorescence microscopy technique based on recording the lifetime of emission of a sample rather than the intensity of emission. bioimaging edam topics Can be done with widefield or confocal. Can be with array or point detectors. Fluorescence lifetime imaging microscopy FRAP Microscopy method for studying kinetics of diffusion of molecules in a sample. Fluorescence localization after photobleaching (FLAP) Fluorescence loss in photobleaching (FLIP) Inverse fluorescence recovery after photobleaching (iFRAP) bioimaging edam topics Can be widefield or confocal. Fluorescence recovery after photobleaching FRET FRET allows to study the distance between light sensitive molecules by monitoring the transfer of energy between them. Electronic energy transfer (EET) Fluorescence resonance energy transfer Single-molecule FRET (smFRET) bioimaging edam topics Can be widefield or confocal fluorescence microscopy. Can be with array or point detectors. Förster resonance energy transfer ICS Particle Image Correlation Spectroscopy (PICS) Raster Image Correlation Spectroscopy (RICS) bioimaging edam topics Image correlation spectroscopy bioimaging edam topics Reinforcement learning bioimaging edam topics Work comments: 28th August 2018 within supervised learning there could be ‘regression’ and ‘classification’ joakim.lindblad 20th March 2019 It's a good question how deep to go. Currently we're going less deep within Topics (which are rather broad fluffy) than the operations. Thus I added a seeAlso to the operation Supervised learning bioimaging edam topics Unsupervised learning Multi-modal imaging Multisensor imaging Correlative imaging Correlative microscopy Hybrid imaging Utilizing different imaging modalities in combination Multimodal imaging Can be just EM or anything. But may also combine optical and electron microscopy of ultra thin serial sections. volumetric microscopy method based on physical serial sectioning. Can be appyied in LM and EM. Work comment: should we even remove it from underneath Tomography and instead put it somewhere to Image Prep? Array tomography AFM Force spectroscopy SFM Scanning force microscopy Atomic force microscopy Cell image informatics Cell image analysis Digital cytology Digital histopathology Digital pathology imaging Telepathology bioimaging edam topics Digital pathology Expansion microscopy relies on a chemical increase in sample size allowing to obtain a high resolution on traditional microscopes. ExM Expansion microscopy Localisation markers are objects placed in the field of view of an imaging system to serve as a reference. Landmarking Landmarks Branding Fiducial markers Localisation beads Finder grids Gridded coverslips Localisation markers Force microscopy Histology studies the anatomy of tissues via microscopy, often followed by image analysis. Histology Interference reflection microscopy Interferometric microscopy Imaging of live processes performed within living animals, typically by multi-photon imaging techniques. Intravital imaging Light field microscopy Imaging mass spectrometry (IMS) MSI Mass spectrometry-based imaging Spatial mass spectrometry Mass spectrometry imaging Holography Structured illumination 2P-MOST MOST Micro-optical sectioning tomography Two-photon micro-optical sectioning microscopy Optical sectioning tomography NSOM Scanning near-field optical microscopy (SNOM) Scattering-type scanning near-field optical microscopy Near-field scanning optical microscopy Creation of localisation markers in 3D in a sample using a near-infrared laser. Near-infrared branding Non-linear microscopy PFM Force measurement microscopy Force sensing optical tweezers Photonic force microscopy Plant image informatics Plant image analysis Coherent anti-Stokes Raman scattering microscopy (CARS) Stimulated Raman Scattering (SRS) Raman spectroscopy SHIM Second-harmonic generation (SHG) Third-harmonic generation (THG) Second-harmonic imaging microscopy SXT Cryo-SXT Cryo-soft X-ray tomography Synchrotron X-ray tomographic microscopy Synchrotron X-ray tomography cSXT Soft X-ray tomography TIRF Type of microscopy using a high angle of incidence of a laser to produce an evanescent field to selectively excite fluorophores in close proximity to the coverslip. TIRFM HiLo microscopy highly inclined and laminated optical sheet (HiLo) Total internal reflection fluorescence microscopy Traction force microscopy X-ray microscope An x-ray microscope uses radiation in the soft x-ray band (approximately 0.2-20 nm wavelength) to produce magnified images. X-ray microscopy Cryogenic focused ion beam (cryo-FIB) milling Focused ion beam (FIB) milling Ablation Airyscan Matrix detector Multi-point detector Multi-point detection microscopy AI Artificial intelligence ANN Dense neural network Feedforward neural network Fully-connected neural network Multi-layer perceptron (MLP) Abbreviation DNN is occassionally used without consensus for either 'Dense neural network' or 'Deep neural network', mutually exclusive terms, therefore it is not included in EDAM. DenseNet (related term of CNN) vs. Dense NN: clarify Artificial neural network Autoencoder network Autoencoder Bayesian network Bayesian inference? Bayesian statistics Blotting Work comments: Xavier Heiligenstein 20th March 2019 related to : aldehyde fixation, methanol fixation, dehydration Matúš Kalaš 20th March 2019 Immunocytochemistry ICC Immunohistochemistry IHC Martin & Laure & Christos Mar 2020: These don't influence analysis, let's not care about these in EDAM. Matus: Anything of those useful for searchability by biologists, to put into Related terms? Or in a comment? Chemical fixation Computed microtomography High-resolution micro-CT Micro computed tomography Micro-computed tomography micro CT micro-CT µCT bioimaging edam topics X-ray microtomography Work comment: See comment elsewhere Computer vision Contrasting agent Work comment: Re Xavier: it's added, to some minimal extent. The consideration is how much the contrasting agents etc. influence the choices of analysis. And the relation to annotation/labelling. Done for now, left for further improvements Contrasting method DenseNet U-Net CNN ConvNet Convolutional neural network <_permanent_id rdf:resource="http://edamontology.org/topic_4017"/> cryo-EM 1.26 A method for studying biomolecules and other structures at very low (cryogenic) temperature using electron microscopy. Cryo electron microscopy Electron cryomicroscopy cryoEM Cryogenic electron microscopy Classification and regression tree Decision tree Decision tree learning Decision tree learning Deconvolution widefield microscopy Feature learning Representation learning Deep learning is part of a broader family of machine learning methods incorporating feature learning or representation learning (techniques that allow a system to automatically discover the representations needed for feature detection or classification from raw data). Deep learning is typically based on artificial neural networks. Check & comment wrt to the broad synonyms. Comment not needed if t's clear from the definition, as it seems to be atm. Deep learning Genetic algorithm Genetic programming Evolutionary algorithm Fluorescence FTIR Fourier-transform infrared spectroscopy Highly automated microscopy to image and analyse large areas and/or large number of samples. Also outside of imaging (as opposed to HCA/HCS), e.g. proteomics, gene expression/transcriptomics, etc. HTS In simple terms, high-content screening (HCS) is the combination of high-throughput screening (HTS) applied to high-content analysis (HCA). High-throughput screening IFC Imaging flow cytometry Instrument calibration Instrument setup A generic concept related to e.g. calibration of instruments (such as microscopes). Applicable also outside of biology. Instrument maintenance Laser capture microdissection (LCM) Laser capture microscopy Laser catapulting Laser dissection microscopy Laser microdissection <_permanent_id rdf:resource="http://edamontology.org/topic_3384"/> 1.4 VT 3.2.13 Medical imaging VT 3.2.14 Nuclear medicine VT 3.2.24 Radiology The use of imaging techniques for clinical purposes for medical research. Nuclear medicine Radiology Medical imaging Cryo-microtomy Cryo-ultramicrotomy Oscilating knife Ultra-microtomy Vibrate Microtomy Molecular imaging OCT is a label free detection technique, that uses low-coherence light to capture micrometer-resolution, two- and three-dimensional images from within scattering tissues. OCT Optical coherence tomography OPT is a form of tomography using visible light to generate 3D image volumes based on absorption (label-free) or fluorescence. OPT Optical tomography Optical computed tomography Optical emission computed tomography Optical tomography optical-CT optical-ECT Optical projection tomography PCI Phase-contrast X-ray imaging Label free Digital Holography Holographic microscopy Holographic tomography Ptychography Phase imaging This technique allows the selective cutting of parts of samples without thermal damage. Laser ablation Laser microsurgery Laser nanosurgery Photoablation Optogenetics Photoconversion Photoswitch photobleaching Photoactivation Photomanipulation Quantitative phase imaging RBF network Radial basis function network Random decision forest Random forest Ratiometric imaging RCM Rescan Re-Scan Re-scan confocal microscopy Gated recurrent unit (GRU) Long short-term memory (LSTM) RNN Recurrent neural network Fast R-CNN Faster R-CNN R-CNN RBF network Region-proposal network Sample preparation process that makes sample transparent cleared tissue Sample clearing Work comments: Xavier Heiligenstein 20th March 2019 Subcategories: room temperature embedding, dehydration, progressive lowering temperature (PLT), freeze-substitution Matúš Kalaš 20th March 2019 Discussion: Clearing, Thinning, Blotting, Embedding synonyms, related terms Microtomy, etc (see also Matthia's comment in Sample thinning) Related term(s) to Volume imaging -- should we add that? In which context(s)? Further discussion Martin, Laure, Nataša: - perhaps concern of another ontology - for further consideration what of that matters for analysis choices (e.g. with the volume) - Martin: how and when slicing is done in EM will influence analysis Sample embedding Sample fixation Sample stabilisation Sample immobilisation Work comments: Xavier Heiligenstein 20th March 2019 This contains the sub categories: microtomy, ultra-microtomy, blotting, vibrating blade sectioning, cryo-microtomy, oscillating, ablation Matthia.Karreman 20th March 2019 Examples of sample thinning blotting (as in vitrobot) microtomy (ultra-, cryo- (ultra), vibratome, oscilating knife, ) ablation (Focus ion beam, laser) Laure 16th October 2019 I have created them but as I am no expert, does it work? Martin: IMHO not a generally used term. See FIB (Ablation), Sectioning Christos: Diff between sectining and thinning: sectioning removes. But results otherwise same. M & C: Terminology is not (yet) standardised around these Let's get back to it with definitions and relations, ... Sample thinning Interactive visual analysis Visual analytics Scientific visualisation Scientific visualization Adaptive optics Intelligent microscopy Smart microscopy Intelligent microscopy uses artificial intelligence; smart microscopy is using a defined algorithm to adapt microscope configuration or imaging parameters. (Robert Haase & consensus) Adaptive microscopy Weakly-supervised learning Semi-supervised learning Single particle analysis (SPA) Single particle cryo-electron microscopy Single-particle cryogenic electron microscopy Enhancement of contrast in biological samples. Histological staining Sample staining Stereology Stereoscopy is a non-digital technique creating the illusion of depth in an image. Stereo imaging Stereoscopics Stereoscopy SVM Support vector machine Label-free sample Unstained sample Radiology? Roentgenology? Röntgenology? Radiography X-ray imaging Ambient ionisation mass spectrometry Ambient ionisation mass spectrometry imaging AP-MALDI imaging Atmospheric pressure scanning microprobe matrix-assisted laser desorption/ionization (AP-SMALDI) imaging Atmospheric pressure matrix-assisted laser desorptaion/ionisation imaging Autoregressive model Bias in machine learning Hopfield network? Statistical Hopfield network? Deep Boltzmann machine (DBM) Restricted Boltzmann machine (RBM) Spike-and-slab RBM Boltzmann machine Chromatography Copula function DESI-MS Desorption electrospray ionisation mass spectrometry DESI imaging DESI IMS DESI MSI Nanospray desorption electrospray ionisation (nano-DESI) imaging Desorption electrospray ionisation imaging DIOS-MS Nanostructure-initiator mass spectrometry Desorption/ionisation-on-silicon mass spectrometry NIMS Desorption/ionisation on silicon (DIOS) DIOS imaging Nanostructure imaging mass spectrometry Diffusion model Discriminative statistical model Flow cytometry GAN Generative adversarial network Generative artificial intelligence (Generative AI, GenAI, GAI) Large generative model Generative statistical model HMM This is a Data concept http://edamontology.org/data_1364 in EDAM! Hidden Markov model Image cytometry Imaging cytometry IMC CyTOF imaging CyTOF tissue imaging Multiplexed ion beam imaging (MIBI™ imaging) Imaging mass cytometry Immunofluorescence IHC Immunohistochemistry Immunostaining ICP-MS Inductively coupled plasma mass spectrometry IR-MALDI imaging Infrared matrix-assisted laser desorption/ionisation imaging LLM Large language model LAESI imaging Laser ablation electrospray ionisation imaging LAESI-MS Laser ablation electrospray ionisation mass spectrometry LA-ICP imaging Laser ablation inductively coupled plasma imaging Laser desorption/ionisation mass spectrometry LDI imaging Laser desorption/ionisation mass spectrometry imaging L-system Lindenmayer system LESA imaging Liquid extraction surface analysis imaging LESA-MS Liquid extraction surface analysis mass spectrometry Cytometry by time of flight (CyTOF) Mass cytometry MALDESI-MS Matrix-assisted laser desorption electrospray ionisation mass spectrometry MALDESI imaging Matrix-assisted laser desorption electrospray ionisation imaging MALDI-IHC Matrix-assisted laser desorption/ionisation immunohistochemistry MALDI-MS Matrix-assisted laser desorption/ionisation mass spectrometry MALDI imaging MALDI imaging mass spectrometry (MALDI IMS) MALDI mass spectrometry imaging (MALDI MSI) Matrix-assisted laser desorption/ionisation imaging Co-detection by indexing (CODEX) Cytometry by cyclic immunofluorescence (CyCIF) Multiplexed immunofluorescence Multiplexed immunohistochemistry Vectra imaging?/ Vectra cytometry? Note that imaging mass cytometry (IMC, ADD EDAM ID HERE) is a special case of multiplexed immunostaining, distinct from both (multiplexed) immunofluorenscence and immunohistochemistry (IHC). Multiplexed immunostaining PGM Structured probabilistic model Probabilistic graphical model Parametric statistics Probability distribution Prompt engineering A generative statistical model that is based on rules. Rule-based generative model A generative statistical model that is based on statistical sampling. Sampling-based generative model SIMS Nanoscale secondary ion mass spectrometry (NanoSIMS) Secondary ion mass spectrometry SIMS imaging Nanoscale secondary ion mass spectrometry imaging Secondary ion mass spectrometry imaging Self-supervised learning Single-cell modality Single-cell data acquisition Spatial metabolomics Spatial proteomics Spatial transcriptomics Spectrometry Stochastic process SALDI imaging Surface-assisted laser desorption/ionisation imaging SALDI-MS Surface-assisted laser desorption/ionisation mass spectrometry Multiplexed cytometry Tissue cytometry Transfer learning Encoder–decoder model Transformer (machine learning) Variational autoencoder EDS Cynthia Arend, Matúš Kalaš EDX EDXS Energy dispersive X-ray analysis (EDXA, EDAX) Energy dispersive X-ray microanalysis (EDXMA) XEDS Energy-dispersive X-ray spectroscopy EELS Electron energy loss spectroscopy Scanning probe microscopy KNN k-NN k-nearest neighbor algorithm k-nearest neighbors algorithm k-nearest neighbour algorithm k-nearest neighbours algorithm k-nearest neighbors k-nearest neighbours MCFoell 2025-01-17T09:40:52.400992Z Dye-based staining H&E MCFoell 2025-01-17T09:42:34.687136Z Hematoxylin and eosin staining LaureP 2025-01-31T14:25:11.525834Z Nipkow disk microscopy Spinning disk confocal microscopy (SDCM) Spinning disk microscopy LaureP 2025-01-31T14:28:16.74497Z Confocal laser scanning microscopy (CLSM) Laser-scanning microscopy (LSM) Point-scanning confocal microscopy Laser-scanning confocal microscopy ESEM Matúš Kalaš 2025-02-14T10:44:46.256118Z Environmental scanning electron microscopy ETEM Matúš Kalaš 2025-02-14T10:50:13.06276Z Environmental transmission electron microscopy Matúš Kalaš 2025-02-21T15:00:09.959365Z Point detection microscopy Matúš Kalaš 2025-03-06T20:05:19.125059Z Sample material separation Diffraction Diffractometer Matúš Kalaš 2025-03-06T20:38:36.513361Z Diffractometry and scattering Adriaan Ludl 2025-03-07T14:11:48.334652Z Label-free imaging Matúš Kalaš 2025-03-11T12:09:28.995236Z Raman imaging Raman microscopy WDS Matúš Kalaš, Harald Hausen 2025-03-11T12:22:33.109874Z Wavelength dispersive X-ray spectroscopy Matúš Kalaš 2025-03-11T12:31:06.55322Z Emission spectroscopy AES Cynthia Arend, Matúš Kalaš 2025-03-11T12:34:09.937003Z Auger electron spectroscopy XPS Matúš Kalaš 2025-03-11T12:35:26.938209Z X-ray photoelectron spectroscopy PIXE spectroscopy Cynthia Arend, Matúš Kalaš 2025-03-11T12:38:03.70413Z Particle-induced X-ray emission spectroscopy EMP Cynthia Arend, Matúš Kalaš 2025-03-11T12:42:38.108916Z Electron micro probe analyzer (EMPA) Electron probe microanalyzer (EPMA) Electron microprobe CL microscopy Matúš Kalaš, Harald Hausen 2025-03-11T16:19:33.899595Z Cathodoluminescence microscopy Matúš Kalaš 2025-03-13T17:12:59.831249Z Backscatter X-ray BSE imaging Cynthia Arend, Matúš Kalaš 2025-03-13T17:17:50.257989Z Backscattered electrons imaging EBSD Cynthia Arend, Matúš Kalaš 2025-03-13T17:21:04.837092Z Electron backscatter diffraction Matúš Kalaš 2025-03-13T17:27:49.636249Z Electron diffractometry and scattering Matúš Kalaš 2025-03-13T17:30:40.817795Z Crystallography Matúš Kalaš 2025-03-13T17:34:35.292336Z Radiocrystallography Röntgencrystallography X-ray crystallography Matúš Kalaš 2025-10-25T22:25:20.838673Z Neuroimaging Matúš Kalaš 2025-08-14T07:35:02.08358Z Macromolecular structure capture Matúš Kalaš 2025-08-14T18:14:59.975003Z Pre-clinical imaging Preclinical imaging STM bianchini 2025-08-15T06:54:49.46901Z Scanning tunneling microscopy is a technique that uses quantum tunneling to image surfaces, often at an atomic level resolution. It works by scanning a sharp tip over a sample's surface and measuring the resulting tunneling current. Spin-polarised scanning tunneling microscopy (SP-STM) Scanning tunneling microscopy Matúš Kalaš 2025-09-17T09:54:41.64113Z Spatial analysis Matúš Kalaš 2025-09-17T09:55:24.67444Z Temporal analysis Matúš Kalaš 2025-10-25T22:36:12.731422Z Plant cell imaging Plant imaging cryo-FIB-SEM Alexandra Zakieva, Harald Hausen, Matúš Kalaš 2025-10-15T12:50:18.372299Z cryo FIB-SEM cryo-FIB SEM cryo-FIB/SEM Cryogenic focused ion beam scanning electron microscopy MINFLUX Matúš Kalaš 2025-10-16T23:37:44.289548Z Minimal fluorescence photon fluxes microscopy CXEM Matúš Kalaš 2025-10-17T00:01:49.784416Z Correlative X-ray imaging and electron microscopy Correlative X-ray and electron microscopy CLXEM Matúš Kalaš 2025-10-17T00:14:16.521896Z Volume correlative light, X-ray, and electron microscopy (Volume CLXEM) Correlative light, X-ray, and electron microscopy CLXM Matúš Kalaš 2025-10-17T00:21:51.837749Z Correlative cryo-fluorescence and cryo-soft X-ray tomography Cryogenic correlative light and X-ray microscopy (Cryo-correlative light and X-ray microscopy, cryo-CLXM) Correlative light and X-ray microscopy ME-SALDI imaging MESALDI imaging Matrix-enhanced surface-assisted laser desorption/ionisation imaging