{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,21]],"date-time":"2025-12-21T06:25:44Z","timestamp":1766298344877,"version":"3.37.3"},"reference-count":40,"publisher":"Oxford University Press (OUP)","issue":"19","license":[{"start":{"date-parts":[[2022,8,17]],"date-time":"2022-08-17T00:00:00Z","timestamp":1660694400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"name":"German Federal Ministry of Education and Research (BMBF) [LiSyM-Cancer","award":["031L0257J\/031L0256C","LiSyM: 031L0035"],"award-info":[{"award-number":["031L0257J\/031L0256C","LiSyM: 031L0035"]}]},{"DOI":"10.13039\/501100001659","name":"German Research Foundation","doi-asserted-by":"crossref","award":["HO 4772\/1-1"],"award-info":[{"award-number":["HO 4772\/1-1"]}],"id":[{"id":"10.13039\/501100001659","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,9,30]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Motivation<\/jats:title><jats:p>Over the last decades, image processing and analysis have become one of the key technologies in systems biology and medicine. The quantification of anatomical structures and dynamic processes in living systems is essential for understanding the complex underlying mechanisms and allows, i.e. the construction of spatio-temporal models that illuminate the interplay between architecture and function. Recently, deep learning significantly improved the performance of traditional image analysis in cases where imaging techniques provide large amounts of data. However, if only a few images are available or qualified annotations are expensive to produce, the applicability of deep learning is still limited.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>We present a novel approach that combines machine learning-based interactive image segmentation using supervoxels with a clustering method for the automated identification of similarly colored images in large image sets which enables a guided reuse of interactively trained classifiers. Our approach solves the problem of deteriorated segmentation and quantification accuracy when reusing trained classifiers which is due to significant color variability prevalent and often unavoidable in biological and medical images. This increase in efficiency improves the suitability of interactive segmentation for larger image sets, enabling efficient quantification or the rapid generation of training data for deep learning with minimal effort. The presented methods are applicable for almost any image type and represent a useful tool for image analysis tasks in general.<\/jats:p><\/jats:sec><jats:sec><jats:title>Availability and implementation<\/jats:title><jats:p>The presented methods are implemented in our image processing software TiQuant which is freely available at tiquant.hoehme.com.<\/jats:p><\/jats:sec><jats:sec><jats:title>Supplementary information<\/jats:title><jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p><\/jats:sec>","DOI":"10.1093\/bioinformatics\/btac547","type":"journal-article","created":{"date-parts":[[2022,8,17]],"date-time":"2022-08-17T13:58:35Z","timestamp":1660744715000},"page":"4622-4628","source":"Crossref","is-referenced-by-count":3,"title":["Guided interactive image segmentation using machine learning and color-based image set clustering"],"prefix":"10.1093","volume":"38","author":[{"given":"Adrian","family":"Friebel","sequence":"first","affiliation":[{"name":"Institute of Computer Science, Leipzig University , Leipzig 04107, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tim","family":"Johann","sequence":"additional","affiliation":[{"name":"IfADo\u2014Leibniz Research Centre for Working Environment and Human Factors , Dortmund 44139, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dirk","family":"Drasdo","sequence":"additional","affiliation":[{"name":"IfADo\u2014Leibniz Research Centre for Working Environment and Human Factors , Dortmund 44139, Germany"},{"name":"INRIA Saclay-\u00cele de France, Group SIMBIOTX , Palaiseau 91120, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9716-9587","authenticated-orcid":false,"given":"Stefan","family":"Hoehme","sequence":"additional","affiliation":[{"name":"Institute of Computer Science, Leipzig University , Leipzig 04107, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2022,8,17]]},"reference":[{"key":"2023041408225252700_","doi-asserted-by":"crossref","first-page":"2274","DOI":"10.1109\/TPAMI.2012.120","article-title":"SLIC superpixels compared to state-of-the-art superpixel methods","volume":"34","author":"Achanta","year":"2012","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell"},{"key":"2023041408225252700_","first-page":"2424","article-title":"Trainable weka segmentation: a machine learning tool for microscopy pixel classification","volume":"33","author":"Arganda-Carreras","year":"2017","journal-title":"Bioinformatics (Oxford, England)"},{"first-page":"1027","year":"2007","author":"Arthur","key":"2023041408225252700_"},{"year":"1972","author":"Barlow","key":"2023041408225252700_"},{"key":"2023041408225252700_","first-page":"180","article-title":"Parallel algorithms via scaled paraboloid structuring functions for spatially-variant and label-set dilations and erosions","author":"Beare","year":"2011"},{"key":"2023041408225252700_","doi-asserted-by":"crossref","first-page":"e1002340","DOI":"10.1371\/journal.pbio.1002340","article-title":"Microscopy image browser: a platform for segmentation and analysis of multidimensional datasets","volume":"14","author":"Belevich","year":"2016","journal-title":"PLoS Biol"},{"key":"2023041408225252700_","doi-asserted-by":"crossref","first-page":"1226","DOI":"10.1038\/s41592-019-0582-9","article-title":"ilastik: interactive machine learning for (bio)image analysis","volume":"16","author":"Berg","year":"2019","journal-title":"Nat. Methods"},{"key":"2023041408225252700_","first-page":"281","article-title":"Random search for hyper-parameter optimization","volume":"13","author":"Bergstra","year":"2012","journal-title":"J. Mach. Learn. Res"},{"key":"2023041408225252700_","first-page":"3121","article-title":"The balanced accuracy and its posterior distribution","author":"Brodersen","year":"2010"},{"key":"2023041408225252700_","first-page":"1649","article-title":"Effective initialization of k-means for color quantization","author":"Celebi","year":"2009"},{"key":"2023041408225252700_","first-page":"2843","volume-title":"Advances in Neural Information Processing Systems 25","author":"Ciresan","year":"2012"},{"key":"2023041408225252700_","first-page":"147","article-title":"Using the triangle inequality to accelerate k-means","author":"Elkan","year":"2003"},{"key":"2023041408225252700_","first-page":"3133","article-title":"Do we need hundreds of classifiers to solve real world classification problems?","volume":"15","author":"Fern\u00e1ndez-Delgado","year":"2014","journal-title":"J. Mach. Learn. Res"},{"key":"2023041408225252700_","first-page":"3234","article-title":"TiQuant: software for tissue analysis, quantification and surface reconstruction","volume":"31","author":"Friebel","year":"2015","journal-title":"Bioinformatics (Oxford, England)"},{"key":"2023041408225252700_","doi-asserted-by":"crossref","first-page":"359","DOI":"10.1198\/016214506000001437","article-title":"Strictly proper scoring rules, prediction, and estimation","volume":"102","author":"Gneiting","year":"2007","journal-title":"J. Am. Stat. Assoc"},{"first-page":"1161","year":"2014","author":"Hammad","key":"2023041408225252700_"},{"key":"2023041408225252700_","first-page":"2961","article-title":"Mask R-CNN","author":"He","year":"2017"},{"key":"2023041408225252700_","first-page":"2020","article-title":"fastER: a user-friendly tool for ultrafast and robust cell segmentation in large-scale microscopy","volume":"33","author":"Hilsenbeck","year":"2017","journal-title":"Bioinformatics (Oxford, England)"},{"key":"2023041408225252700_","doi-asserted-by":"crossref","first-page":"10371","DOI":"10.1073\/pnas.0909374107","article-title":"Prediction and validation of cell alignment along microvessels as order principle to restore tissue architecture in liver regeneration","volume":"107","author":"Hoehme","year":"2010","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"2023041408225252700_","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1002\/1520-684X(200007)31:8<33::AID-SCJ4>3.0.CO;2-C","article-title":"Color quantization using the fast K-means algorithm","volume":"31","author":"Kasuga","year":"2000","journal-title":"Syst. Comp. Jpn"},{"key":"2023041408225252700_","first-page":"1097","volume-title":"Advances in Neural Information Processing Systems 25","author":"Krizhevsky","year":"2012"},{"key":"2023041408225252700_","doi-asserted-by":"crossref","first-page":"60","DOI":"10.1016\/j.media.2017.07.005","article-title":"A survey on deep learning in medical image analysis","volume":"42","author":"Litjens","year":"2017","journal-title":"Med. Image Anal"},{"key":"2023041408225252700_","doi-asserted-by":"crossref","first-page":"637","DOI":"10.1038\/nmeth.2083","article-title":"Annotated high-throughput microscopy image sets for validation","volume":"9","author":"Ljosa","year":"2012","journal-title":"Nat. Methods"},{"key":"2023041408225252700_","doi-asserted-by":"crossref","first-page":"129","DOI":"10.1109\/TIT.1982.1056489","article-title":"Least squares quantization in PCM","volume":"28","author":"Lloyd","year":"1982","journal-title":"IEEE Trans. Inform. Theory"},{"key":"2023041408225252700_","first-page":"3431","article-title":"Fully convolutional networks for semantic segmentation","author":"Long","year":"2015"},{"key":"2023041408225252700_","doi-asserted-by":"crossref","first-page":"327","DOI":"10.1109\/34.761263","article-title":"Evaluation of methods for ridge and valley detection","volume":"21","author":"Lopez","year":"1999","journal-title":"IEEE Trans. Pattern Anal. Machine Intell"},{"key":"2023041408225252700_","doi-asserted-by":"crossref","first-page":"474","DOI":"10.1109\/TMI.2011.2171705","article-title":"Supervoxel-based segmentation of mitochondria in EM image stacks with learned shape features","volume":"31","author":"Lucchi","year":"2012","journal-title":"IEEE Trans. Med. Imaging"},{"key":"2023041408225252700_","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1016\/j.jsb.2017.02.007","article-title":"SuRVoS: super-region volume segmentation workbench","volume":"198","author":"Luengo","year":"2017","journal-title":"J. Struct. Biol"},{"key":"2023041408225252700_","first-page":"821","article-title":"Retrieving similar image using color moment feature detector and K-means clustering of remote sensing images","author":"Maheshwary","year":"2008"},{"key":"2023041408225252700_","first-page":"532","article-title":"Image clustering using color moments, histogram, edge and K-means clustering","volume":"2","author":"Malakar","year":"2013","journal-title":"Int. J. Sci. Res"},{"key":"2023041408225252700_","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1002\/(SICI)1097-0320(19970801)28:4<289::AID-CYTO3>3.0.CO;2-7","article-title":"Applying watershed algorithms to the segmentation of clustered nuclei","volume":"28","author":"Malpica","year":"1998","journal-title":"Cytometry"},{"key":"2023041408225252700_","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1016\/S1361-8415(96)80007-7","article-title":"Deformable models in medical image analysis: a survey","volume":"1","author":"McInerney","year":"1996","journal-title":"Med. Image Anal"},{"key":"2023041408225252700_","first-page":"625","article-title":"Predicting good probabilities with supervised learning","author":"Niculescu-Mizil","year":"2005"},{"key":"2023041408225252700_","doi-asserted-by":"crossref","first-page":"355","DOI":"10.1016\/S0734-189X(87)80186-X","article-title":"Adaptive histogram equalization and its variations","volume":"39","author":"Pizer","year":"1987","journal-title":"Comput. Vis. Graph. Image Process"},{"key":"2023041408225252700_","first-page":"61","article-title":"Probabilistic outputs for support vector machines and comparisons to regularized likelihood methods","volume":"10","author":"Platt","year":"1999","journal-title":"Adv. Large Margin Class"},{"key":"2023041408225252700_","first-page":"10","article-title":"Learning a classification model for segmentation","author":"Ren","year":"2003"},{"key":"2023041408225252700_","first-page":"234","volume-title":"Medical Image Computing and Computer-Assisted Intervention - MICCAI","author":"Ronneberger","year":"2015"},{"key":"2023041408225252700_","first-page":"291","article-title":"Quantification of histochemical staining by color deconvolution","volume":"23","author":"Ruifrok","year":"2001","journal-title":"Anal. Quant. Cytol. Histol"},{"key":"2023041408225252700_","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.cviu.2017.03.007","article-title":"Superpixels: an evaluation of the state-of-the-art","volume":"166","author":"Stutz","year":"2018","journal-title":"Comput. Vis. Image Underst"},{"key":"2023041408225252700_","first-page":"1531","volume-title":"Hepatology","author":"Vartak","year":"2021"}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/advance-article-pdf\/doi\/10.1093\/bioinformatics\/btac547\/45477447\/btac547.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/38\/19\/4622\/49885117\/btac547.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/38\/19\/4622\/49885117\/btac547.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,11,25]],"date-time":"2023-11-25T21:48:00Z","timestamp":1700948880000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/38\/19\/4622\/6670619"}},"subtitle":[],"editor":[{"given":"Janet","family":"Kelso","sequence":"additional","affiliation":[],"role":[{"role":"editor","vocabulary":"crossref"}]}],"short-title":[],"issued":{"date-parts":[[2022,8,17]]},"references-count":40,"journal-issue":{"issue":"19","published-print":{"date-parts":[[2022,9,30]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btac547","relation":{},"ISSN":["1367-4803","1367-4811"],"issn-type":[{"type":"print","value":"1367-4803"},{"type":"electronic","value":"1367-4811"}],"subject":[],"published-other":{"date-parts":[[2022,10,1]]},"published":{"date-parts":[[2022,8,17]]}}}