{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T22:26:13Z","timestamp":1784154373155,"version":"3.55.0"},"reference-count":39,"publisher":"Elsevier BV","issue":"4","license":[{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2027,3,7]],"date-time":"2027-03-07T00:00:00Z","timestamp":1804377600000},"content-version":"am","delay-in-days":340,"URL":"http:\/\/www.elsevier.com\/open-access\/userlicense\/1.0\/"}],"funder":[{"DOI":"10.13039\/100023015","name":"Advanced Research Projects Agency for Health","doi-asserted-by":"publisher","award":["D24AC00357"],"award-info":[{"award-number":["D24AC00357"]}],"id":[{"id":"10.13039\/100023015","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100023015","name":"Advanced Research Projects Agency for Health","doi-asserted-by":"publisher","award":["D25AC00140"],"award-info":[{"award-number":["D25AC00140"]}],"id":[{"id":"10.13039\/100023015","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100014039","name":"US Department of Defense Prostate Cancer Research Program","doi-asserted-by":"publisher","award":["W81XWH-14-2-0183"],"award-info":[{"award-number":["W81XWH-14-2-0183"]}],"id":[{"id":"10.13039\/100014039","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100014039","name":"US Department of Defense Prostate Cancer Research Program","doi-asserted-by":"publisher","award":["W81XWH-20-1-0851"],"award-info":[{"award-number":["W81XWH-20-1-0851"]}],"id":[{"id":"10.13039\/100014039","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100014039","name":"US Department of Defense Prostate Cancer Research Program","doi-asserted-by":"publisher","award":["W81XWH-18-10358"],"award-info":[{"award-number":["W81XWH-18-10358"]}],"id":[{"id":"10.13039\/100014039","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000062","name":"National Institute of Diabetes and Digestive and Kidney Diseases","doi-asserted-by":"publisher","award":["R01DK138948"],"award-info":[{"award-number":["R01DK138948"]}],"id":[{"id":"10.13039\/100000062","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000054","name":"National Institutes of Health National Cancer Institute","doi-asserted-by":"publisher","award":["R01CA202752"],"award-info":[{"award-number":["R01CA202752"]}],"id":[{"id":"10.13039\/100000054","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000054","name":"National Institutes of Health National Cancer Institute","doi-asserted-by":"publisher","award":["R01CA257612"],"award-info":[{"award-number":["R01CA257612"]}],"id":[{"id":"10.13039\/100000054","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000054","name":"National Institutes of Health National Cancer Institute","doi-asserted-by":"publisher","award":["U01CA269181"],"award-info":[{"award-number":["U01CA269181"]}],"id":[{"id":"10.13039\/100000054","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000054","name":"National Institutes of Health National Cancer Institute","doi-asserted-by":"publisher","award":["1U01CA248226"],"award-info":[{"award-number":["1U01CA248226"]}],"id":[{"id":"10.13039\/100000054","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000054","name":"National Institutes of Health National Cancer Institute","doi-asserted-by":"publisher","award":["R01CA216579"],"award-info":[{"award-number":["R01CA216579"]}],"id":[{"id":"10.13039\/100000054","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000054","name":"National Institutes of Health National Cancer Institute","doi-asserted-by":"publisher","award":["R01CA268287"],"award-info":[{"award-number":["R01CA268287"]}],"id":[{"id":"10.13039\/100000054","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000054","name":"National Institutes of Health National Cancer Institute","doi-asserted-by":"publisher","award":["R01CA220581"],"award-info":[{"award-number":["R01CA220581"]}],"id":[{"id":"10.13039\/100000054","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000054","name":"National Institutes of Health National Cancer Institute","doi-asserted-by":"publisher","award":["R01CA208236"],"award-info":[{"award-number":["R01CA208236"]}],"id":[{"id":"10.13039\/100000054","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000054","name":"National Institutes of Health National Cancer Institute","doi-asserted-by":"publisher","award":["1U54CA254566"],"award-info":[{"award-number":["1U54CA254566"]}],"id":[{"id":"10.13039\/100000054","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000054","name":"National Institutes of Health National Cancer Institute","doi-asserted-by":"publisher","award":["R01CA249992"],"award-info":[{"award-number":["R01CA249992"]}],"id":[{"id":"10.13039\/100000054","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000054","name":"National Institutes of Health National Cancer Institute","doi-asserted-by":"publisher","award":["1U01CA239055"],"award-info":[{"award-number":["1U01CA239055"]}],"id":[{"id":"10.13039\/100000054","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000054","name":"National Institutes of Health National Cancer Institute","doi-asserted-by":"publisher","award":["R01CA268207"],"award-info":[{"award-number":["R01CA268207"]}],"id":[{"id":"10.13039\/100000054","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000738","name":"US Department of Veterans Affairs","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000738","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000070","name":"National Institute of Biomedical Imaging and Bioengineering","doi-asserted-by":"publisher","award":["R01EB031002"],"award-info":[{"award-number":["R01EB031002"]}],"id":[{"id":"10.13039\/100000070","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100002491","name":"Bristol-Myers Squibb","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100002491","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100004325","name":"AstraZeneca","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100004325","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000005","name":"U.S. Department of Defense","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000005","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000050","name":"National Heart Lung and Blood Institute","doi-asserted-by":"publisher","award":["R01HL15807101A1"],"award-info":[{"award-number":["R01HL15807101A1"]}],"id":[{"id":"10.13039\/100000050","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000050","name":"National Heart Lung and Blood Institute","doi-asserted-by":"publisher","award":["1R01HL15127701A1"],"award-info":[{"award-number":["1R01HL15127701A1"]}],"id":[{"id":"10.13039\/100000050","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["mp.uscap.org","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Modern Pathology"],"published-print":{"date-parts":[[2026,4]]},"DOI":"10.1016\/j.modpat.2026.100975","type":"journal-article","created":{"date-parts":[[2026,2,14]],"date-time":"2026-02-14T00:19:02Z","timestamp":1771028342000},"page":"100975","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":1,"title":["Detection of Prostate Cancer in 3-Dimensional Pathology Datasets via Generative Immunolabeling"],"prefix":"10.1016","volume":"39","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6646-353X","authenticated-orcid":false,"given":"Robert B.","family":"Serafin","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jennifer Salguero","family":"Lopez","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Suet","family":"Chow","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rui","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yujie","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Elena","family":"Baraznenok","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lydia","family":"Lan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kevin","family":"Bishop","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michelle","family":"Downes","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xavier","family":"Farre","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lawrence D.","family":"True","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Priti","family":"Lal","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anant","family":"Madabhushi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jonathan T.C.","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.modpat.2026.100975_bib1","article-title":"Cancer facts & figures 2024","year":"2024","journal-title":"CA Cancer J Clin"},{"key":"10.1016\/j.modpat.2026.100975_bib2","first-page":"125","article-title":"Classification of prostatic carcinomas","volume":"50","author":"Gleason","year":"1966","journal-title":"Cancer Chemother Rep"},{"key":"10.1016\/j.modpat.2026.100975_bib3","doi-asserted-by":"crossref","first-page":"433","DOI":"10.1111\/apm.12533","article-title":"International Society of Urological Pathology (ISUP) grading of prostate cancer\u2014an ISUP consensus on contemporary grading","volume":"124","author":"Egevad","year":"2016","journal-title":"APMIS"},{"key":"10.1016\/j.modpat.2026.100975_bib4","doi-asserted-by":"crossref","first-page":"461","DOI":"10.5858\/arpa.2020-0015-RA","article-title":"The 2019 Genitourinary Pathology Society (GUPS) white paper on contemporary grading of prostate cancer","volume":"145","author":"Epstein","year":"2021","journal-title":"Arch Pathol Lab Med"},{"key":"10.1016\/j.modpat.2026.100975_bib5","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1053\/hupa.2001.21135","article-title":"Interobserver reproducibility of Gleason grading of prostatic carcinoma: general pathologist","volume":"32","author":"Allsbrook","year":"2001","journal-title":"Hum Pathol"},{"key":"10.1016\/j.modpat.2026.100975_bib6","doi-asserted-by":"crossref","first-page":"420","DOI":"10.1080\/21681805.2016.1206619","article-title":"Interobserver variability in Gleason histological grading of prostate cancer","volume":"50","author":"Ozkan","year":"2016","journal-title":"Scand J Urol"},{"key":"10.1016\/j.modpat.2026.100975_bib7","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1111\/his.12008","article-title":"Standardization of Gleason grading among 337 European pathologists","volume":"62","author":"Egevad","year":"2013","journal-title":"Histopathology"},{"key":"10.1016\/j.modpat.2026.100975_bib8","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1038\/s41551-020-00681-x","article-title":"Harnessing non-destructive 3D pathology","volume":"5","author":"Liu","year":"2021","journal-title":"Nat Biomed Eng"},{"key":"10.1016\/j.modpat.2026.100975_bib9","doi-asserted-by":"crossref","first-page":"1122","DOI":"10.1038\/s41596-023-00934-4","article-title":"An end-to-end workflow for nondestructive 3D pathology","volume":"19","author":"Bishop","year":"2024","journal-title":"Nat Protoc"},{"key":"10.1016\/j.modpat.2026.100975_bib10","doi-asserted-by":"crossref","first-page":"896","DOI":"10.1016\/j.cell.2014.10.010","article-title":"iDISCO: a simple, rapid method to immunolabel large tissue samples for volume imaging","volume":"159","author":"Renier","year":"2014","journal-title":"Cell"},{"key":"10.1016\/j.modpat.2026.100975_bib11","doi-asserted-by":"crossref","first-page":"1709","DOI":"10.1038\/nprot.2015.085","article-title":"Advanced CUBIC protocols for whole-brain and whole-body clearing and imaging","volume":"10","author":"Susaki","year":"2015","journal-title":"Nat Protoc"},{"key":"10.1016\/j.modpat.2026.100975_bib12","doi-asserted-by":"crossref","first-page":"0084","DOI":"10.1038\/s41551-017-0084","article-title":"Light-sheet microscopy for slide-free non-destructive pathology of large clinical specimens","volume":"1","author":"Glaser","year":"2017","journal-title":"Nat Biomed Eng"},{"key":"10.1016\/j.modpat.2026.100975_bib13","doi-asserted-by":"crossref","first-page":"6605","DOI":"10.1364\/BOE.408684","article-title":"Multi-resolution open-top light-sheet microscopy to enable efficient 3D pathology workflows","volume":"11","author":"Barner","year":"2020","journal-title":"Biomed Opt Express"},{"key":"10.1016\/j.modpat.2026.100975_bib14","doi-asserted-by":"crossref","first-page":"2781","DOI":"10.1038\/s41467-019-10534-0","article-title":"Multi-immersion open-top light-sheet microscope for high-throughput imaging of cleared tissues","volume":"10","author":"Glaser","year":"2019","journal-title":"Nat Commun"},{"key":"10.1016\/j.modpat.2026.100975_bib15","doi-asserted-by":"crossref","first-page":"613","DOI":"10.1038\/s41592-022-01468-5","article-title":"A hybrid open-top light-sheet microscope for versatile multi-scale imaging of cleared tissues","volume":"19","author":"Glaser","year":"2022","journal-title":"Nat Methods"},{"key":"10.1016\/j.modpat.2026.100975_bib16","doi-asserted-by":"crossref","first-page":"2502","DOI":"10.1016\/j.cell.2024.03.035","article-title":"Analysis of 3D pathology samples using weakly supervised AI","volume":"187","author":"Song","year":"2024","journal-title":"Cell"},{"key":"10.1016\/j.modpat.2026.100975_bib17","doi-asserted-by":"crossref","first-page":"334","DOI":"10.1158\/0008-5472.CAN-21-2843","article-title":"Prostate cancer risk stratification via nondestructive 3D pathology with deep learning\u2013assisted gland analysis","volume":"82","author":"Xie","year":"2022","journal-title":"Cancer Res"},{"key":"10.1016\/j.modpat.2026.100975_bib18","doi-asserted-by":"crossref","first-page":"390","DOI":"10.1002\/path.6090","article-title":"Nondestructive 3D pathology with analysis of nuclear features for prostate cancer risk assessment","volume":"260","author":"Serafin","year":"2023","journal-title":"J Pathol"},{"key":"10.1016\/j.modpat.2026.100975_bib19","doi-asserted-by":"crossref","DOI":"10.1016\/j.labinv.2023.100265","article-title":"Visual assessment of 2-dimensional levels within 3-dimensional pathology data sets of prostate needle biopsies reveals substantial spatial heterogeneity","volume":"103","author":"Koyuncu","year":"2023","journal-title":"Lab Invest"},{"key":"10.1016\/j.modpat.2026.100975_bib20","doi-asserted-by":"crossref","first-page":"457","DOI":"10.1016\/j.euf.2016.05.009","article-title":"Nuclear shape and architecture in benign fields predict biochemical recurrence in prostate cancer patients following radical prostatectomy: preliminary findings","volume":"3","author":"Lee","year":"2017","journal-title":"Eur Urol Focus"},{"key":"10.1016\/j.modpat.2026.100975_bib21","doi-asserted-by":"crossref","first-page":"1470","DOI":"10.1002\/pros.20983","article-title":"Evidence for field cancerization of the prostate","volume":"69","author":"Nonn","year":"2009","journal-title":"Prostate"},{"key":"10.1016\/j.modpat.2026.100975_bib22","doi-asserted-by":"crossref","DOI":"10.1155\/2012\/302894","article-title":"Markers of field cancerization: proposed clinical applications in prostate biopsies","volume":"2012","author":"Trujillo","year":"2012","journal-title":"Prostate Cancer"},{"key":"10.1016\/j.modpat.2026.100975_bib23","doi-asserted-by":"crossref","first-page":"46","DOI":"10.11604\/pamj.2015.20.46.3926","article-title":"Expression of some selected cytokeratins and Ki67 protein in prostatic tumor: can these be used as tumor markers","volume":"20","author":"Adisa","year":"2015","journal-title":"Pan Afr Med J"},{"key":"10.1016\/j.modpat.2026.100975_bib24","doi-asserted-by":"crossref","first-page":"43","DOI":"10.4103\/jpi.jpi_103_20","article-title":"Generative adversarial networks in digital pathology and histopathological image processing: a review","volume":"12","author":"Jose","year":"2021","journal-title":"J Pathol Inform"},{"key":"10.1016\/j.modpat.2026.100975_bib25","article-title":"BCI: breast cancer immunohistochemical image generation through pyramid Pix2pix","author":"Liu","year":"2022","journal-title":"Preprint"},{"key":"10.1016\/j.modpat.2026.100975_bib26","doi-asserted-by":"crossref","DOI":"10.1016\/j.modpat.2023.100369","article-title":"Generative adversarial networks in digital histopathology: current applications, limitations, ethical considerations, and future directions","volume":"37","author":"Alajaji","year":"2024","journal-title":"Mod Pathol"},{"key":"10.1016\/j.modpat.2026.100975_bib27","doi-asserted-by":"crossref","DOI":"10.1038\/s41598-020-74500-3","article-title":"SHIFT: speedy histological-to-immunofluorescent translation of a tumor signature enabled by deep learning","volume":"10","author":"Burlingame","year":"2020","journal-title":"Sci Rep"},{"key":"10.1016\/j.modpat.2026.100975_bib28","doi-asserted-by":"crossref","first-page":"466","DOI":"10.1038\/s41551-019-0362-y","article-title":"Virtual histological staining of unlabelled tissue-autofluorescence images via deep learning","volume":"3","author":"Rivenson","year":"2019","journal-title":"Nat Biomed Eng"},{"key":"10.1016\/j.modpat.2026.100975_bib29","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1038\/s41377-019-0129-y","article-title":"PhaseStain: the digital staining of label-free quantitative phase microscopy images using deep learning","volume":"8","author":"Rivenson","year":"2019","journal-title":"Light Sci Appl"},{"key":"10.1016\/j.modpat.2026.100975_bib30","article-title":"Video-to-video synthesis","author":"Wang","year":"2018","journal-title":"Preprint"},{"key":"10.1016\/j.modpat.2026.100975_bib31","doi-asserted-by":"crossref","first-page":"870","DOI":"10.1038\/s41592-019-0501-0","article-title":"BigStitcher: reconstructing high-resolution image datasets of cleared and expanded samples","volume":"16","author":"H\u00f6rl","year":"2019","journal-title":"Nat Methods"},{"key":"10.1016\/j.modpat.2026.100975_bib32","doi-asserted-by":"crossref","first-page":"671","DOI":"10.1038\/nmeth.2089","article-title":"NIH Image to ImageJ: 25 years of image analysis","volume":"9","author":"Schneider","year":"2012","journal-title":"Nat Methods"},{"key":"10.1016\/j.modpat.2026.100975_bib33","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0233198","article-title":"FalseColor-Python: a rapid intensity-leveling and digital-staining package for fluorescence-based slide-free digital pathology","volume":"15","author":"Serafin","year":"2020","journal-title":"PLoS One"},{"key":"10.1016\/j.modpat.2026.100975_bib34","doi-asserted-by":"crossref","DOI":"10.1038\/s41598-017-17204-5","article-title":"QuPath: open source software for digital pathology image analysis","volume":"7","author":"Bankhead","year":"2017","journal-title":"Sci Rep"},{"key":"10.1016\/j.modpat.2026.100975_bib35","doi-asserted-by":"crossref","DOI":"10.1117\/1.JBO.29.3.036001","article-title":"Direct three-dimensional segmentation of prostate glands with nnU-Net","volume":"29","author":"Wang","year":"2024","journal-title":"J Biomed Opt"},{"key":"10.1016\/j.modpat.2026.100975_bib36","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1038\/s41592-020-01008-z","article-title":"nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation","volume":"18","author":"Isensee","year":"2021","journal-title":"Nat Methods"},{"key":"10.1016\/j.modpat.2026.100975_bib37","doi-asserted-by":"crossref","DOI":"10.1038\/s41598-024-79602-w","article-title":"Generating and evaluating synthetic data in digital pathology through diffusion models","volume":"14","author":"Pozzi","year":"2024","journal-title":"Sci Rep"},{"key":"10.1016\/j.modpat.2026.100975_bib38","doi-asserted-by":"crossref","first-page":"1621","DOI":"10.1364\/BOE.416731","article-title":"Towards in-vivo label-free detection of brain tumor margins with epi-illumination tomographic quantitative phase imaging","volume":"12","author":"Costa","year":"2021","journal-title":"Biomed Opt Express"},{"key":"10.1016\/j.modpat.2026.100975_bib39","doi-asserted-by":"crossref","first-page":"231","DOI":"10.1146\/annurev-anchem-091222-092734","article-title":"Nondestructive 3D pathology with light-sheet fluorescence microscopy for translational research and clinical assays","volume":"16","author":"Liu","year":"2023","journal-title":"Annu Rev Anal Chem (Palo Alto Calif)"}],"container-title":["Modern Pathology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0893395226000189?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0893395226000189?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,6,22]],"date-time":"2026-06-22T11:34:40Z","timestamp":1782128080000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0893395226000189"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4]]},"references-count":39,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2026,4]]}},"alternative-id":["S0893395226000189"],"URL":"https:\/\/doi.org\/10.1016\/j.modpat.2026.100975","relation":{},"ISSN":["0893-3952"],"issn-type":[{"value":"0893-3952","type":"print"}],"subject":[],"published":{"date-parts":[[2026,4]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Detection of Prostate Cancer in 3-Dimensional Pathology Datasets via Generative Immunolabeling","name":"articletitle","label":"Article Title"},{"value":"Modern Pathology","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.modpat.2026.100975","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 United States & Canadian Academy of Pathology. Published by Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"100975"}}