{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,22]],"date-time":"2025-02-22T00:45:41Z","timestamp":1740185141656,"version":"3.37.3"},"reference-count":41,"publisher":"Oxford University Press (OUP)","issue":"Supplement_1","license":[{"start":{"date-parts":[[2022,6,27]],"date-time":"2022-06-27T00:00:00Z","timestamp":1656288000000},"content-version":"vor","delay-in-days":3,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62020106004","92048301","61906133"],"award-info":[{"award-number":["62020106004","92048301","61906133"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,6,24]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Motivation<\/jats:title><jats:p>The presence of tumor cell clusters in pleural effusion may be a signal of cancer metastasis. The instance segmentation of single cell from cell clusters plays a pivotal role in cluster cell analysis. However, current cell segmentation methods perform poorly for cluster cells due to the overlapping\/touching characters of clusters, multiple instance properties of cells, and the poor generalization ability of the models.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>In this article, we propose a contour constraint instance segmentation framework (CC framework) for cluster cells based on a cluster cell combination enhancement module. The framework can accurately locate each instance from cluster cells and realize high-precision contour segmentation under a few samples. Specifically, we propose the contour attention constraint module to alleviate over- and under-segmentation among individual cell-instance boundaries. In addition, to evaluate the framework, we construct a pleural effusion cluster cell dataset including 197 high-quality samples. The quantitative results show that the numeric result of APmask is &amp;gt; 90%, a more than 10% increase compared with state-of-the-art semantic segmentation algorithms. From the qualitative results, we can observe that our method rarely has segmentation errors.<\/jats:p><\/jats:sec>","DOI":"10.1093\/bioinformatics\/btac219","type":"journal-article","created":{"date-parts":[[2022,4,14]],"date-time":"2022-04-14T11:10:15Z","timestamp":1649934615000},"page":"i53-i59","source":"Crossref","is-referenced-by-count":0,"title":["Synthetic-to-real: instance segmentation of clinical cluster cells with unlabeled synthetic training"],"prefix":"10.1093","volume":"38","author":[{"given":"Meng","family":"Zhao","sequence":"first","affiliation":[{"name":"Engineering Research Center of Learning-Based Intelligent System (Ministry of Education), The Key Laboratory of Computer Vision and System (Ministry of Education), and the School of Computer Science and Engineering, Tianjin University of Technology , Tianjin 300384, China"}]},{"given":"Siyu","family":"Wang","sequence":"additional","affiliation":[{"name":"Engineering Research Center of Learning-Based Intelligent System (Ministry of Education), The Key Laboratory of Computer Vision and System (Ministry of Education), and the School of Computer Science and Engineering, Tianjin University of Technology , Tianjin 300384, China"}]},{"given":"Fan","family":"Shi","sequence":"additional","affiliation":[{"name":"Engineering Research Center of Learning-Based Intelligent System (Ministry of Education), The Key Laboratory of Computer Vision and System (Ministry of Education), and the School of Computer Science and Engineering, Tianjin University of Technology , Tianjin 300384, China"}]},{"given":"Chen","family":"Jia","sequence":"additional","affiliation":[{"name":"Engineering Research Center of Learning-Based Intelligent System (Ministry of Education), The Key Laboratory of Computer Vision and System (Ministry of Education), and the School of Computer Science and Engineering, Tianjin University of Technology , Tianjin 300384, China"}]},{"given":"Xuguo","family":"Sun","sequence":"additional","affiliation":[{"name":"School of Medical Laboratory, Tianjin Medical University , Tianjin 300204, China"}]},{"given":"Shengyong","family":"Chen","sequence":"additional","affiliation":[{"name":"Engineering Research Center of Learning-Based Intelligent System (Ministry of Education), The Key Laboratory of Computer Vision and System (Ministry of Education), and the School of Computer Science and Engineering, Tianjin University of Technology , Tianjin 300384, China"}]}],"member":"286","published-online":{"date-parts":[[2022,6,27]]},"reference":[{"year":"2018","author":"Baur","key":"2023041407544620000_"},{"key":"2023041407544620000_","doi-asserted-by":"crossref","first-page":"i42","DOI":"10.1093\/bioinformatics\/btab336","article-title":"Investigation of refined CNN ensemble learning for anti-cancer drug sensitivity prediction","volume":"37","author":"Bazgir","year":"2021","journal-title":"Bioinformatics"},{"first-page":"9157","year":"2019","author":"Bolya","key":"2023041407544620000_"},{"first-page":"1483","year":"2021","author":"Cai","key":"2023041407544620000_"},{"year":"2020","author":"Chen","key":"2023041407544620000_"},{"first-page":"279","year":"2020","author":"Chen","key":"2023041407544620000_"},{"first-page":"15334","year":"2021","author":"Cheng","key":"2023041407544620000_"},{"key":"2023041407544620000_","doi-asserted-by":"crossref","first-page":"158679","DOI":"10.1109\/ACCESS.2020.3020393","article-title":"A fast and accurate algorithm for nuclei instance segmentation in microscopy images","volume":"8","author":"Cheng","year":"2020","journal-title":"IEEE Access"},{"year":"2017","author":"DeVries","key":"2023041407544620000_"},{"year":"2020","author":"Fan","key":"2023041407544620000_"},{"key":"2023041407544620000_","doi-asserted-by":"crossref","first-page":"4151","DOI":"10.1016\/j.patcog.2012.05.006","article-title":"Unsupervised segmentation and classification of cervical cell images","volume":"45","author":"Gen\u00e7tav","year":"2012","journal-title":"Pattern Recogn."},{"key":"2023041407544620000_","doi-asserted-by":"crossref","first-page":"101563","DOI":"10.1016\/j.media.2019.101563","article-title":"Hover-net: simultaneous segmentation and classification of nuclei in multi-tissue histology images","volume":"58","author":"Graham","year":"2019","journal-title":"Med. 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