{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:17:05Z","timestamp":1750220225774,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":31,"publisher":"ACM","license":[{"start":{"date-parts":[[2022,3,18]],"date-time":"2022-03-18T00:00:00Z","timestamp":1647561600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"Natural Science Foundation of China","award":["No.61773325 and 61806173"],"award-info":[{"award-number":["No.61773325 and 61806173"]}]},{"name":"Joint Funds of 5th Round of Health and Education Research Program of Fujian Province","award":["No. 2019-WJ-41"],"award-info":[{"award-number":["No. 2019-WJ-41"]}]},{"name":"Young Teacher Education Research Project of Fujian","award":["No. JT180435"],"award-info":[{"award-number":["No. JT180435"]}]},{"name":"Industry-University Cooperation Project of Fujian Science and Technology Department","award":["No. 2021H6035"],"award-info":[{"award-number":["No. 2021H6035"]}]},{"DOI":"10.13039\/501100003392","name":"Natural Science Foundation of Fujian Province","doi-asserted-by":"publisher","award":["No.2021J011191 and 2019J05123"],"award-info":[{"award-number":["No.2021J011191 and 2019J05123"]}],"id":[{"id":"10.13039\/501100003392","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2022,3,18]]},"DOI":"10.1145\/3532213.3532291","type":"proceedings-article","created":{"date-parts":[[2022,7,13]],"date-time":"2022-07-13T13:29:18Z","timestamp":1657718958000},"page":"515-521","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["CDE-Net: A semi-supervised nucleus instance segmentation method based on center deviation estimation"],"prefix":"10.1145","author":[{"given":"Yi","family":"Yan","sequence":"first","affiliation":[{"name":"Computer and Information Engineering, Xiamen University of Technology, China and Fujian Key Laboratory of Pattern Recognition and Image Understanding, Xiamen University of Technology, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Da-Han","family":"Wang","sequence":"additional","affiliation":[{"name":"Computer and Information Engineering, Xiamen University of Technology, China and Fujian Key Laboratory of Pattern Recognition and Image Understanding, Xiamen University of Technology, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haili","family":"Ye","sequence":"additional","affiliation":[{"name":"Computer and Information Engineering, Xiamen University of Technology, China and Fujian Key Laboratory of Pattern Recognition and Image Understanding, Xiamen University of Technology, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shunzhi","family":"Zhu","sequence":"additional","affiliation":[{"name":"Computer and Information Engineering, Xiamen University of Technology, China and Fujian Key Laboratory of Pattern Recognition and Image Understanding, Xiamen University of Technology, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianmin","family":"Li","sequence":"additional","affiliation":[{"name":"Computer and Information Engineering, Xiamen University of Technology, China and Fujian Key Laboratory of Pattern Recognition and Image Understanding, Xiamen University of Technology, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2022,7,13]]},"reference":[{"key":"e_1_3_2_1_1_1","first-page":"1196","volume":"201","author":"Korsuk Sirinukunwattana","unstructured":"Korsuk Sirinukunwattana , Shan e Ahmed Raza, Yee-Wah Tsang , David R. J. Snead , Ian A. Cree , Nasir M. Rajpoot . Locality Sensitive Deep Learning for Detection and Classification of Nuclei in Routine Colon Cancer Histology Images. IEEE Trans. Medical Imaging. 201 6;35(5): 1196 - 1206 Korsuk Sirinukunwattana, Shan e Ahmed Raza, Yee-Wah Tsang, David R. J. Snead, Ian A. Cree, Nasir M. Rajpoot. Locality Sensitive Deep Learning for Detection and Classification of Nuclei in Routine Colon Cancer Histology Images. IEEE Trans. Medical Imaging. 2016;35(5): 1196-1206","journal-title":"Routine Colon Cancer Histology Images. IEEE Trans. Medical Imaging."},{"key":"e_1_3_2_1_2_1","first-page":"10513","volume":"200","author":"Mitchell P S","unstructured":"Mitchell P S , Parkin R K , Kroh E M , Circulating microRNAs as stable blood-based markers for cancer detection. Proceedings of the National Academy of Sciences of the United States of America , 200 8;105(30): 10513 - 10518 . Mitchell P S, Parkin R K, Kroh E M, Circulating microRNAs as stable blood-based markers for cancer detection. Proceedings of the National Academy of Sciences of the United States of America, 2008;105(30):10513-10518.","journal-title":"America"},{"key":"e_1_3_2_1_3_1","first-page":"3993","volume":"200","author":"Costes S V","unstructured":"Costes S V , Daelemans D , Cho E H , Automatic and quantitative measurement of protein-protein colocalization in live cells. Biophysical Journal. 200 4;86(6): 3993 - 4003 . Costes S V, Daelemans D, Cho E H, Automatic and quantitative measurement of protein-protein colocalization in live cells. Biophysical Journal. 2004;86(6):3993-4003.","journal-title":"Biophysical Journal."},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"crossref","unstructured":"Johannes S Ignacio A C Erwin F Verena K Mark L Tobias P Stephan P Curtis R Stephan S Benjamin S Fiji: an open-source platform for biological-image analysis. Nature methods. 2012;9(7):676.  Johannes S Ignacio A C Erwin F Verena K Mark L Tobias P Stephan P Curtis R Stephan S Benjamin S Fiji: an open-source platform for biological-image analysis. Nature methods. 2012;9(7):676.","DOI":"10.1038\/nmeth.2019"},{"key":"e_1_3_2_1_5_1","first-page":"1559","volume":"201","author":"Weinberg R A","unstructured":"Weinberg R A , Chaffer C L. A Perspective on Cancer Cell Metastasis. Science , 201 1;331(6024): 1559 - 1564 . Weinberg R A, Chaffer C L. A Perspective on Cancer Cell Metastasis. Science, 2011;331(6024): 1559-1564.","journal-title":"Cancer Cell Metastasis. Science"},{"key":"e_1_3_2_1_6_1","first-page":"1448","volume":"201","author":"Sahirzeeshan Ali","unstructured":"Sahirzeeshan Ali , Anant Madabhushi. An Integrated Region-, Boundary -, Shape-Based Active Contour for Multiple Object Overlap Resolution in Histological Imagery. IEEE Trans. Medical Imaging. 201 2;31(7): 1448 - 1460 . Sahirzeeshan Ali, Anant Madabhushi. An Integrated Region-, Boundary-, Shape-Based Active Contour for Multiple Object Overlap Resolution in Histological Imagery. IEEE Trans. Medical Imaging. 2012;31(7): 1448-1460.","journal-title":"Histological Imagery. IEEE Trans. Medical Imaging."},{"key":"e_1_3_2_1_7_1","first-page":"4568","volume":"201","author":"Marina E.","unstructured":"Marina E. Plissiti , Christophoros Nikou. Overlapping Cell Nuclei Segmentation Using a Spatially Adaptive Active Physical Model. IEEE Trans. Image Process. 201 2;21(11): 4568 - 4580 . Marina E. Plissiti, Christophoros Nikou. Overlapping Cell Nuclei Segmentation Using a Spatially Adaptive Active Physical Model. IEEE Trans. Image Process. 2012;21(11): 4568-4580.","journal-title":"Spatially Adaptive Active Physical Model. IEEE Trans. Image Process."},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"crossref","unstructured":"Afaf Tareef Yang Song Min-Zhao Lee David Dagan Feng Mei Chen Tom Weidong Cai. Morphological Filtering and Hierarchical Deformation for Partially Overlapping Cell Segmentation. DICTA. 2015;1-7.  Afaf Tareef Yang Song Min-Zhao Lee David Dagan Feng Mei Chen Tom Weidong Cai. Morphological Filtering and Hierarchical Deformation for Partially Overlapping Cell Segmentation. DICTA. 2015;1-7.","DOI":"10.1109\/DICTA.2015.7371285"},{"key":"e_1_3_2_1_9_1","first-page":"3983","volume":"200","author":"Alhajj M","unstructured":"Alhajj M , Wicha M S , Benitohernandez A , Erratum:Prospective identification of tumorigenic breast cancer cells. Proceedings of the National Academy of Sciences of the United States of America. 200 3; 3983 - 3988 . Alhajj M, Wicha M S, Benitohernandez A, Erratum:Prospective identification of tumorigenic breast cancer cells. Proceedings of the National Academy of Sciences of the United States of America. 2003;3983-3988.","journal-title":"America."},{"key":"e_1_3_2_1_10_1","first-page":"973","volume":"200","author":"Prince M","unstructured":"Prince M , Sivanandan R , Kaczorowski A , Identification of a subpopulation of cells with cancer stem cell properties in head and neck squamous cell carcinoma. Proc Natl Acad Sci U S A , 200 7;104(3): 973 - 978 . Prince M, Sivanandan R, Kaczorowski A, Identification of a subpopulation of cells with cancer stem cell properties in head and neck squamous cell carcinoma. Proc Natl Acad Sci U S A, 2007;104(3):973-978.","journal-title":"Proc Natl Acad Sci U S A"},{"key":"e_1_3_2_1_11_1","first-page":"1051","volume":"201","author":"Min Zhang","unstructured":"Min Zhang , Teresa Wu, Kevin M. Bennett . Small Blob Identification in Medical Images Using Regional Features From Optimum Scale. IEEE Trans. Biomed. Eng. 201 5;62(4): 1051 - 1062 . Min Zhang, Teresa Wu, Kevin M. Bennett. Small Blob Identification in Medical Images Using Regional Features From Optimum Scale. IEEE Trans. Biomed. Eng. 2015;62(4):1051-1062.","journal-title":"Medical Images Using Regional Features From Optimum Scale. IEEE Trans. Biomed. Eng."},{"key":"e_1_3_2_1_12_1","first-page":"1661","volume":"201","author":"Hui Kong N.","unstructured":"Hui Kong , Metin N. Gurcan , Kamel Belkacem-Boussaid. Partitioning Histopathological Images: An Integrated Framework for Supervised Color-Texture Segmentation and Cell Splitting. IEEE Trans. Medical Imaging. 201 1;30(9): 1661 - 1677 . Hui Kong, Metin N. Gurcan, Kamel Belkacem-Boussaid. Partitioning Histopathological Images: An Integrated Framework for Supervised Color-Texture Segmentation and Cell Splitting. IEEE Trans. Medical Imaging. 2011;30(9):1661-1677.","journal-title":"Cell Splitting. IEEE Trans. Medical Imaging."},{"key":"e_1_3_2_1_13_1","first-page":"74","volume-title":"2020 BiO-Net: Learning Recurrent Bi-directional Connections for Encoder-Decoder Architecture (MICCAI)","author":"Xiang T","unstructured":"Xiang T , Zhang C , Liu D , 2020 BiO-Net: Learning Recurrent Bi-directional Connections for Encoder-Decoder Architecture (MICCAI) pp 74 - 84 Xiang T, Zhang C, Liu D, 2020 BiO-Net: Learning Recurrent Bi-directional Connections for Encoder-Decoder Architecture (MICCAI) pp 74-84"},{"key":"e_1_3_2_1_14_1","first-page":"234","volume-title":"2015 U-Net: Convolutional Networks for Biomedical Image Segmentation (MICCAI)","author":"Ronneberger O","unstructured":"Ronneberger O , Fischer P , Brox T. 2015 U-Net: Convolutional Networks for Biomedical Image Segmentation (MICCAI) pp 234 - 241 Ronneberger O, Fischer P, Brox T. 2015 U-Net: Convolutional Networks for Biomedical Image Segmentation (MICCAI) pp 234-241"},{"key":"e_1_3_2_1_15_1","first-page":"451","volume-title":"2019 Instance Segmentation of Biomedical Images with an Object-Aware Embedding Learned with Local Constraints (MICCAI)","author":"Chen L","unstructured":"Chen L , Strauch M , Merhof D. 2019 Instance Segmentation of Biomedical Images with an Object-Aware Embedding Learned with Local Constraints (MICCAI) pp 451 - 459 Chen L, Strauch M, Merhof D. 2019 Instance Segmentation of Biomedical Images with an Object-Aware Embedding Learned with Local Constraints (MICCAI) pp 451-459"},{"key":"e_1_3_2_1_16_1","volume-title":"Adapting Mask-RCNN for Automatic Nucleus Segmentation","author":"Johnson J W","year":"2018","unstructured":"Johnson J W . ( 2018 ) \u201c Adapting Mask-RCNN for Automatic Nucleus Segmentation \u201d [Online] Available: https:\/\/arxiv.org\/abs\/1805.00500 Johnson J W. (2018) \u201cAdapting Mask-RCNN for Automatic Nucleus Segmentation\u201d [Online] Available: https:\/\/arxiv.org\/abs\/1805.00500"},{"key":"e_1_3_2_1_17_1","first-page":"1","volume":"201","author":"Kumar N","unstructured":"Kumar N , Verma R , Sharma S, A Dataset and a Technique for Generalized Nucleus Segmentation for Computational Pathology. IEEE Transactions on Medical Imaging. 201 7; 1 - 1 Kumar N, Verma R, Sharma S, A Dataset and a Technique for Generalized Nucleus Segmentation for Computational Pathology. IEEE Transactions on Medical Imaging. 2017;1-1","journal-title":"Medical Imaging."},{"key":"e_1_3_2_1_18_1","volume-title":"SRPN: similarity-based region proposal networks for nuclei and cells detection in histology images","author":"Sun Y","year":"2021","unstructured":"Sun Y , Huang X , Zhou H , ( 2021 ) \u201c SRPN: similarity-based region proposal networks for nuclei and cells detection in histology images \u201d [Online] Available: https:\/\/arxiv.org\/abs\/2106.13556v1 Sun Y, Huang X, Zhou H, (2021) \u201cSRPN: similarity-based region proposal networks for nuclei and cells detection in histology images\u201d [Online] Available: https:\/\/arxiv.org\/abs\/2106.13556v1"},{"key":"e_1_3_2_1_19_1","volume-title":"Pyramid Medical Transformer for Medical Image Segmentation","author":"Zhang Z","year":"2021","unstructured":"Zhang Z , Sun B , Zhang W. ( 2021 ) \u201c Pyramid Medical Transformer for Medical Image Segmentation \u201d [Online] Available: https:\/\/arxiv.org\/abs\/2104.14702v2 Zhang Z, Sun B, Zhang W. (2021) \u201cPyramid Medical Transformer for Medical Image Segmentation\u201d [Online] Available: https:\/\/arxiv.org\/abs\/2104.14702v2"},{"key":"e_1_3_2_1_20_1","unstructured":"Rpenter A E Jones T R Lamprecht M R Cell Profiler: image analysis software for identifying and quantifying cell phenotypes. Genome Biology 2006;7  Rpenter A E Jones T R Lamprecht M R Cell Profiler: image analysis software for identifying and quantifying cell phenotypes. Genome Biology 2006;7"},{"key":"e_1_3_2_1_21_1","first-page":"731","volume-title":"Kyunghyun Paeng 2019 PseudoEdgeNet: Nuclei Segmentation only with Point Annotations (MICCAI)","author":"Inwan Yoo","unstructured":"Inwan Yoo , Donggeun Yoo , Kyunghyun Paeng 2019 PseudoEdgeNet: Nuclei Segmentation only with Point Annotations (MICCAI) pp 731 - 739 Inwan Yoo, Donggeun Yoo, Kyunghyun Paeng 2019 PseudoEdgeNet: Nuclei Segmentation only with Point Annotations (MICCAI) pp 731-739"},{"key":"e_1_3_2_1_22_1","first-page":"135","volume":"201","author":"Hao Chen","unstructured":"Hao Chen , Xiaojuan Qi, Lequan Yu , Qi Dou, Jing Qin , Pheng-Ann Heng. DCAN: Deep contour-aware networks for object instance segmentation from histology images. Medical Image Anal. 201 7;36: 135 - 146 . Hao Chen, Xiaojuan Qi, Lequan Yu, Qi Dou, Jing Qin, Pheng-Ann Heng. DCAN: Deep contour-aware networks for object instance segmentation from histology images. Medical Image Anal. 2017;36:135-146.","journal-title":"Medical Image Anal."},{"key":"e_1_3_2_1_23_1","first-page":"228","volume-title":"2018 BESNet: Boundary-Enhanced Segmentation of Cells in Histopathological Images (MICCAI)","author":"Oda H","unstructured":"Oda H , Roth H R , Chiba K , 2018 BESNet: Boundary-Enhanced Segmentation of Cells in Histopathological Images (MICCAI) pp 228 - 236 Oda H, Roth H R, Chiba K, 2018 BESNet: Boundary-Enhanced Segmentation of Cells in Histopathological Images (MICCAI) pp 228-236"},{"key":"e_1_3_2_1_24_1","first-page":"682","volume-title":"2019 CIA-Net: Robust Nuclei Instance Segmentation with Contour-Aware Information Aggregation (IPMI)","author":"Zhou Y","unstructured":"Zhou Y , Onder O F , Dou Q , 2019 CIA-Net: Robust Nuclei Instance Segmentation with Contour-Aware Information Aggregation (IPMI) pp 682 - 693 Zhou Y, Onder O F, Dou Q, 2019 CIA-Net: Robust Nuclei Instance Segmentation with Contour-Aware Information Aggregation (IPMI) pp 682-693"},{"key":"e_1_3_2_1_25_1","first-page":"640","volume":"201","author":"Long J","unstructured":"Long J , Shelhamer E , Darrell T. Fully Convolutional Networks for Semantic Segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence , 201 5;39(4): 640 - 651 Long J, Shelhamer E, Darrell T. Fully Convolutional Networks for Semantic Segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2015;39(4):640-651","journal-title":"Machine Intelligence"},{"key":"e_1_3_2_1_26_1","first-page":"3","volume-title":"Nima Tajbakhsh, Jianming Liang. 2018 UNet++: A Nested U-Net Architecture for Medical Image Segmentation (DLMIA)","author":"Zongwei Zhou","unstructured":"Zongwei Zhou , Md Mahfuzur Rahman Siddiquee , Nima Tajbakhsh, Jianming Liang. 2018 UNet++: A Nested U-Net Architecture for Medical Image Segmentation (DLMIA) pp 3 - 11 Zongwei Zhou, Md Mahfuzur Rahman Siddiquee, Nima Tajbakhsh, Jianming Liang. 2018 UNet++: A Nested U-Net Architecture for Medical Image Segmentation (DLMIA) pp 3-11"},{"key":"e_1_3_2_1_27_1","first-page":"770","volume-title":"2016 Deep Residual Learning for Image Recognition (CVPR)","author":"Kaiming He","unstructured":"Kaiming He , Xiangyu Zhang, Shaoqing Ren , Jian Sun. 2016 Deep Residual Learning for Image Recognition (CVPR) pp 770 - 778 Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun. 2016 Deep Residual Learning for Image Recognition (CVPR) pp 770-778"},{"key":"e_1_3_2_1_28_1","first-page":"108","volume-title":"Liang-Chieh Chen 2020 Axial-DeepLab: Stand-Alone Axial-Attention for Panoptic Segmentation (ECCV)","author":"Huiyu Wang","unstructured":"Huiyu Wang , Yukun Zhu, Bradley Green , Hartwig Adam, Alan L. Yuille , Liang-Chieh Chen 2020 Axial-DeepLab: Stand-Alone Axial-Attention for Panoptic Segmentation (ECCV) pp 108 - 126 Huiyu Wang, Yukun Zhu, Bradley Green, Hartwig Adam, Alan L. Yuille, Liang-Chieh Chen 2020 Axial-DeepLab: Stand-Alone Axial-Attention for Panoptic Segmentation (ECCV) pp 108-126"},{"key":"e_1_3_2_1_29_1","first-page":"36","volume-title":"Patel 2021 Medical Transformer: Gated Axial-Attention for Medical Image Segmentation (MICCAI)","author":"Jeya Maria Jose Valanarasu","unstructured":"Jeya Maria Jose Valanarasu , Poojan Oza, Ilker Hacihaliloglu , Vishal M. Patel 2021 Medical Transformer: Gated Axial-Attention for Medical Image Segmentation (MICCAI) pp 36 - 46 Jeya Maria Jose Valanarasu, Poojan Oza, Ilker Hacihaliloglu, Vishal M. Patel 2021 Medical Transformer: Gated Axial-Attention for Medical Image Segmentation (MICCAI) pp 36-46"},{"key":"e_1_3_2_1_30_1","volume-title":"Pyramid Medical Transformer for Medical Image Segmentation\" [Online] Available: https:\/\/arxiv.org\/abs\/2104.14702","author":"Zhang Z","year":"2021","unstructured":"Zhang Z , Sun B , Zhang W. ( 2021 ) \" Pyramid Medical Transformer for Medical Image Segmentation\" [Online] Available: https:\/\/arxiv.org\/abs\/2104.14702 Zhang Z, Sun B, Zhang W. (2021) \"Pyramid Medical Transformer for Medical Image Segmentation\" [Online] Available: https:\/\/arxiv.org\/abs\/2104.14702"},{"key":"e_1_3_2_1_31_1","first-page":"341","volume-title":"2020 Instance-Aware Self-supervised Learning for Nuclei Segmentation. (MICCAI)","author":"Xie X","unstructured":"Xie X , Chen J , Li Y X , Shen L L , Ma K , Zheng Y F . 2020 Instance-Aware Self-supervised Learning for Nuclei Segmentation. (MICCAI) pp 341 - 350 Xie X, Chen J, Li Y X, Shen L L, Ma K, Zheng Y F. 2020 Instance-Aware Self-supervised Learning for Nuclei Segmentation. (MICCAI) pp 341-350"}],"event":{"name":"ICCAI '22: 2022 8th International Conference on Computing and Artificial Intelligence","acronym":"ICCAI '22","location":"Tianjin China"},"container-title":["Proceedings of the 8th International Conference on Computing and Artificial Intelligence"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3532213.3532291","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3532213.3532291","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T19:30:08Z","timestamp":1750188608000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3532213.3532291"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,3,18]]},"references-count":31,"alternative-id":["10.1145\/3532213.3532291","10.1145\/3532213"],"URL":"https:\/\/doi.org\/10.1145\/3532213.3532291","relation":{},"subject":[],"published":{"date-parts":[[2022,3,18]]},"assertion":[{"value":"2022-07-13","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}