{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,5]],"date-time":"2026-08-05T07:45:55Z","timestamp":1785915955470,"version":"3.56.0"},"reference-count":31,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,6,9]],"date-time":"2026-06-09T00:00:00Z","timestamp":1780963200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100014188","name":"Korea Ministry of Science and ICT","doi-asserted-by":"publisher","award":["RS-2024-00440802"],"award-info":[{"award-number":["RS-2024-00440802"]}],"id":[{"id":"10.13039\/501100014188","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100014188","name":"Korea Ministry of Science and ICT","doi-asserted-by":"publisher","award":["NRF-2022R1A2C2091160"],"award-info":[{"award-number":["NRF-2022R1A2C2091160"]}],"id":[{"id":"10.13039\/501100014188","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100022807","name":"Division of Research, Innovation, Synergies and Education","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100022807","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003725","name":"National Research Foundation of Korea","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100003725","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002701","name":"Korea Ministry of Education","doi-asserted-by":"publisher","award":["RS-2025-25436827"],"award-info":[{"award-number":["RS-2025-25436827"]}],"id":[{"id":"10.13039\/501100002701","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002701","name":"Korea Ministry of Education","doi-asserted-by":"publisher","award":["2026-RISE-10-006"],"award-info":[{"award-number":["2026-RISE-10-006"]}],"id":[{"id":"10.13039\/501100002701","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Array"],"published-print":{"date-parts":[[2026,7]]},"DOI":"10.1016\/j.array.2026.101006","type":"journal-article","created":{"date-parts":[[2026,6,10]],"date-time":"2026-06-10T07:41:31Z","timestamp":1781077291000},"page":"101006","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Stable and unstable chromosomal aberration detection system for biodosimetry"],"prefix":"10.1016","volume":"30","author":[{"given":"Junghun","family":"Han","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Inkyung","family":"Lee","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yousun","family":"Chung","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sejung","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"3","key":"10.1016\/j.array.2026.101006_bib1","first-page":"371","article-title":"Stable and unstable chromosome aberrations measured after occupational exposure to ionizing radiation and ultrasound","volume":"48","author":"Fu\u010di\u0107","year":"2007","journal-title":"Croat Med J"},{"issue":"2","key":"10.1016\/j.array.2026.101006_bib2","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1007\/s00411-016-0647-4","article-title":"Cytogenetic effects of radioiodine therapy: a 20-year follow-up study","volume":"55","author":"Livingston","year":"2016","journal-title":"Radiat Environ Biophys"},{"issue":"2","key":"10.1016\/j.array.2026.101006_bib3","doi-asserted-by":"crossref","first-page":"143","DOI":"10.1093\/oxfordjournals.rpd.a006422","article-title":"Stable and unstable chromosomal aberrations among Finnish nuclear power plant workers","volume":"93","author":"Lindholm","year":"2001","journal-title":"Radiat Protect Dosim"},{"issue":"1","key":"10.1016\/j.array.2026.101006_bib4","first-page":"14","article-title":"Stable and unstable chromosome aberrations in humans and other mammals in relation to the problems of biological dosimetry","volume":"48","author":"Elisova","year":"2008","journal-title":"Radiatsionnaya Biol Radioekologiya"},{"issue":"2","key":"10.1016\/j.array.2026.101006_bib5","first-page":"168","article-title":"Cytogenetic biodosimetry: what it is and how we do it","volume":"19","author":"Wong","year":"2013","journal-title":"Hong Kong Med J"},{"issue":"1","key":"10.1016\/j.array.2026.101006_bib6","first-page":"39","article-title":"Dicentric and translocation analysis for retrospective dose estimation in humans exposed to ionising radiation during the Chernobyl nuclear power plant accident","volume":"311","author":"Salassidis","year":"1994","journal-title":"Mutat Res"},{"issue":"2","key":"10.1016\/j.array.2026.101006_bib7","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1038\/sj.jea.7500008","article-title":"How radiation-specific is the dicentric assay?","volume":"9","author":"Hoffmann","year":"1999","journal-title":"J Expo Anal Environ Epidemiol"},{"issue":"1","key":"10.1016\/j.array.2026.101006_bib8","doi-asserted-by":"crossref","first-page":"285","DOI":"10.1007\/s11063-021-10629-0","article-title":"A new convolutional neural network architecture for automatic segmentation of overlapping human chromosomes","volume":"54","author":"Song","year":"2022","journal-title":"Neural Process Lett"},{"key":"10.1016\/j.array.2026.101006_bib9","series-title":"Medical image computing and computer-assisted intervention - MICCAI 2015","first-page":"234","article-title":"U-Net: convolutional networks for biomedical image segmentation","volume":"vol. 9351","author":"Ronneberger","year":"2015"},{"issue":"12","key":"10.1016\/j.array.2026.101006_bib10","doi-asserted-by":"crossref","first-page":"2481","DOI":"10.1109\/TPAMI.2016.2644615","article-title":"SegNet: a deep convolutional encoder-decoder architecture for image segmentation","volume":"39","author":"Badrinarayanan","year":"2017","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"3","key":"10.1016\/j.array.2026.101006_bib11","doi-asserted-by":"crossref","first-page":"269","DOI":"10.1088\/0952-4746\/23\/3\/304","article-title":"Stable chromosome aberration frequencies in men occupationally exposed to radiation","volume":"23","author":"Tawn","year":"2003","journal-title":"J Radiol Prot"},{"issue":"1","key":"10.1016\/j.array.2026.101006_bib12","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1093\/oxfordjournals.rpd.a006638","article-title":"FISH cytogenetics and the future of radiation biodosimetry","volume":"97","author":"Tucker","year":"2001","journal-title":"Radiat Protect Dosim"},{"key":"10.1016\/j.array.2026.101006_bib13","doi-asserted-by":"crossref","DOI":"10.1016\/j.mrgentox.2021.503419","article-title":"Chromosome aberration dynamics in breast cancer patients treated with radiotherapy: implications for radiation biodosimetry","volume":"872","author":"Lee","year":"2021","journal-title":"Mutat Res Genet Toxicol Environ Mutagen"},{"issue":"9","key":"10.1016\/j.array.2026.101006_bib14","doi-asserted-by":"crossref","first-page":"971","DOI":"10.1080\/09553000110050065","article-title":"Detection of stable chromosome aberrations by FISH in A-bomb survivors: comparison with previous solid Giemsa staining data on the same 230 individuals","volume":"77","author":"Nakano","year":"2001","journal-title":"Int J Radiat Biol"},{"issue":"12","key":"10.1016\/j.array.2026.101006_bib15","doi-asserted-by":"crossref","first-page":"3920","DOI":"10.1109\/TMI.2020.3007642","article-title":"DeepACEv2: automated chromosome enumeration in metaphase cell images using deep convolutional neural networks","volume":"39","author":"Xiao","year":"2020","journal-title":"IEEE Trans Med Imag"},{"key":"10.1016\/j.array.2026.101006_bib16","series-title":"2016 IEEE conference on computer vision and pattern recognition","first-page":"770","article-title":"Deep residual learning for image recognition","author":"He","year":"2016"},{"key":"10.1016\/j.array.2026.101006_bib17","series-title":"2017 IEEE conference on computer vision and pattern recognition","first-page":"2117","article-title":"Feature pyramid networks for object detection","author":"Lin","year":"2017"},{"issue":"6","key":"10.1016\/j.array.2026.101006_bib18","doi-asserted-by":"crossref","first-page":"1137","DOI":"10.1109\/TPAMI.2016.2577031","article-title":"Faster R-CNN: towards real-time object detection with region proposal networks","volume":"39","author":"Ren","year":"2017","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"10.1016\/j.array.2026.101006_bib19","doi-asserted-by":"crossref","first-page":"157727","DOI":"10.1109\/ACCESS.2020.3019937","article-title":"Automated system for chromosome karyotyping to recognize the most common numerical abnormalities using deep learning","volume":"8","author":"Al-Kharraz","year":"2020","journal-title":"IEEE Access"},{"key":"10.1016\/j.array.2026.101006_bib20","series-title":"2017 IEEE conference on computer vision and pattern recognition","first-page":"7263","article-title":"YOLO9000: better, faster, stronger","author":"Redmon","year":"2017"},{"key":"10.1016\/j.array.2026.101006_bib21","series-title":"International conference on learning representations. ICLR","article-title":"Very deep convolutional networks for large-scale image recognition","author":"Simonyan","year":"2015"},{"key":"10.1016\/j.array.2026.101006_bib22","series-title":"2022 IEEE international conference on big data. Big Data","first-page":"5288","article-title":"Swin-TCNet: a vision transformer-based method for automated chromosomal object detection","author":"Kuo","year":"2022"},{"key":"10.1016\/j.array.2026.101006_bib23","series-title":"2021 IEEE\/CVF international conference on computer vision","first-page":"9992","article-title":"Swin transformer: hierarchical vision transformer using shifted windows","author":"Liu","year":"2021"},{"key":"10.1016\/j.array.2026.101006_bib24","series-title":"2020 IEEE\/CVF conference on computer vision and pattern recognition","first-page":"10781","article-title":"EfficientDet: scalable and efficient object detection","author":"Tan","year":"2020"},{"key":"10.1016\/j.array.2026.101006_bib25","first-page":"14569","article-title":"Scalable adaptive computation for iterative generation","volume":"vol.202","author":"Jabri","year":"2023"},{"key":"10.1016\/j.array.2026.101006_bib26","series-title":"Advances in neural information processing systems","first-page":"6840","article-title":"Denoising diffusion probabilistic models","volume":"vol. 33","author":"Ho","year":"2020"},{"key":"10.1016\/j.array.2026.101006_bib27","series-title":"2019 IEEE winter conference on applications of computer vision","first-page":"1262","article-title":"Improved mixed-example data augmentation","author":"Summers","year":"2019"},{"key":"10.1016\/j.array.2026.101006_bib28","article-title":"YOLOv4: optimal speed and accuracy of object detection","author":"Bochkovskiy","year":"2020","journal-title":"arXiv preprint arXiv 2004 10934"},{"key":"10.1016\/j.array.2026.101006_bib29","article-title":"NMS strikes back","author":"Ouyang-Zhang","year":"2022","journal-title":"arXiv preprint arXiv 2212 06137"},{"key":"10.1016\/j.array.2026.101006_bib30","first-page":"213","article-title":"End-to-end object detection with transformers","volume":"vol.12346","author":"Carion","year":"2020"},{"key":"10.1016\/j.array.2026.101006_bib31","series-title":"Advances in neural information processing systems","first-page":"6626","article-title":"GANs trained by a two time-scale update rule converge to a local Nash equilibrium","volume":"vol. 30","author":"Heusel","year":"2017"}],"container-title":["Array"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2590005626003292?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2590005626003292?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,8,5]],"date-time":"2026-08-05T06:54:14Z","timestamp":1785912854000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S2590005626003292"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7]]},"references-count":31,"alternative-id":["S2590005626003292"],"URL":"https:\/\/doi.org\/10.1016\/j.array.2026.101006","relation":{},"ISSN":["2590-0056"],"issn-type":[{"value":"2590-0056","type":"print"}],"subject":[],"published":{"date-parts":[[2026,7]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Stable and unstable chromosomal aberration detection system for biodosimetry","name":"articletitle","label":"Article Title"},{"value":"Array","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.array.2026.101006","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 The Authors. Published by Elsevier Inc.","name":"copyright","label":"Copyright"}],"article-number":"101006"}}