{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:08:47Z","timestamp":1750219727938,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":14,"publisher":"ACM","license":[{"start":{"date-parts":[[2022,11,10]],"date-time":"2022-11-10T00:00:00Z","timestamp":1668038400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2022,11,10]]},"DOI":"10.1145\/3576938.3576940","type":"proceedings-article","created":{"date-parts":[[2023,3,15]],"date-time":"2023-03-15T09:20:36Z","timestamp":1678872036000},"page":"8-12","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["3D Binary Lesion Mask Parsing"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9641-9399","authenticated-orcid":false,"given":"Yi-Qing","family":"Wang","sequence":"first","affiliation":[{"name":"IBM Watson Health Imaging, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1704-2317","authenticated-orcid":false,"given":"Giovanni","family":"Palma","sequence":"additional","affiliation":[{"name":"IBM Watson Health Imaging, France"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2023,3,15]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"The morphological approach to segmentation: the watershed transformation. Mathematical morphology in image processing 34","author":"Beucher Serge","year":"1993","unstructured":"Serge Beucher and Fernand Meyer. 1993. The morphological approach to segmentation: the watershed transformation. Mathematical morphology in image processing 34 (1993), 433\u2013481."},{"key":"e_1_3_2_1_2_1","unstructured":"Patrick Bilic Patrick\u00a0Ferdinand Christ Eugene Vorontsov Grzegorz Chlebus Hao Chen Qi Dou Chi-Wing Fu Xiao Han Pheng-Ann Heng J\u00fcrgen Hesser Samuel Kadoury Tomasz\u00a0K. Konopczynski Miao Le Chunming Li Xiaomeng Li Jana Lipkov\u00e1 John\u00a0S. Lowengrub Hans Meine Jan\u00a0Hendrik Moltz Chris Pal Marie Piraud Xiaojuan Qi Jin Qi Markus Rempfler Karsten Roth Andrea Schenk Anjany Sekuboyina Ping Zhou Christian H\u00fclsemeyer Marcel Beetz Florian Ettlinger Felix Gr\u00fcn Georgios Kaissis Fabian Loh\u00f6fer Rickmer Braren Julian Holch Felix Hofmann Wieland\u00a0H. Sommer Volker Heinemann Colin Jacobs Gabriel Efrain\u00a0Humpire Mamani Bram van Ginneken Gabriel Chartrand An Tang Michal Drozdzal Avi Ben-Cohen Eyal Klang Michal\u00a0Marianne Amitai Eli Konen Hayit Greenspan Johan Moreau Alexandre Hostettler Luc Soler Refael Vivanti Adi Szeskin Naama Lev-Cohain Jacob Sosna Leo Joskowicz and Bjoern\u00a0H. Menze. 2019. The Liver Tumor Segmentation Benchmark (LiTS). CoRR abs\/1901.04056(2019). arxiv:1901.04056http:\/\/arxiv.org\/abs\/1901.04056"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-018-33860-7"},{"volume-title":"Introduction to algorithms","author":"Cormen H.","key":"e_1_3_2_1_4_1","unstructured":"Thomas\u00a0H. Cormen, Charles\u00a0E. Leiserson, Ronald\u00a0L. Rivest, and Clifford Stein. 2009. Introduction to algorithms. MIT press."},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2004.824224"},{"key":"e_1_3_2_1_6_1","volume-title":"RA-UNet: A hybrid deep attention-aware network to extract liver and tumor in CT scans. Frontiers in Bioengineering and Biotechnology","author":"Jin Qiangguo","year":"2020","unstructured":"Qiangguo Jin, Zhaopeng Meng, Changming Sun, Hui Cui, and Ran Su. 2020. RA-UNet: A hybrid deep attention-aware network to extract liver and tumor in CT scans. Frontiers in Bioengineering and Biotechnology (2020), 1471."},{"key":"e_1_3_2_1_7_1","volume-title":"H-DenseUNet: hybrid densely connected UNet for liver and tumor segmentation from CT volumes","author":"Li Xiaomeng","year":"2018","unstructured":"Xiaomeng Li, Hao Chen, Xiaojuan Qi, Qi Dou, Chi-Wing Fu, and Pheng-Ann Heng. 2018. H-DenseUNet: hybrid densely connected UNet for liver and tumor segmentation from CT volumes. IEEE transactions on medical imaging 37, 12 (2018), 2663\u20132674."},{"volume-title":"Understanding and using linear programming","author":"Matousek Jiri","key":"e_1_3_2_1_8_1","unstructured":"Jiri Matousek and Bernd G\u00e4rtner. 2006. Understanding and using linear programming. Springer Science & Business Media."},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1137\/0105003"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2021.3075752"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-87196-3_48"},{"key":"e_1_3_2_1_12_1","volume-title":"International Conference on Medical Image Computing and Computer-Assisted Intervention. Springer, 512\u2013522","author":"Tang Youbao","year":"2020","unstructured":"Youbao Tang, Yuxing Tang, Yingying Zhu, Jing Xiao, and Ronald\u00a0M Summers. 2020. E2Net: An Edge Enhanced Network for Accurate Liver and Tumor Segmentation on CT Scans. In International Conference on Medical Image Computing and Computer-Assisted Intervention. Springer, 512\u2013522."},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00125"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"crossref","unstructured":"Jianpeng Zhang Yutong Xie Pingping Zhang Hao Chen Yong Xia and Chunhua Shen. 2019. Light-Weight Hybrid Convolutional Network for Liver Tumor Segmentation.. In IJCAI Vol.\u00a019. 4271\u20134277.","DOI":"10.24963\/ijcai.2019\/593"}],"event":{"name":"DMIP 2022: 2022 5th International Conference on Digital Medicine and Image Processing","acronym":"DMIP 2022","location":"Kyoto Japan"},"container-title":["Proceedings of the 2022 5th International Conference on Digital Medicine and Image Processing"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3576938.3576940","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3576938.3576940","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T16:36:24Z","timestamp":1750178184000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3576938.3576940"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,11,10]]},"references-count":14,"alternative-id":["10.1145\/3576938.3576940","10.1145\/3576938"],"URL":"https:\/\/doi.org\/10.1145\/3576938.3576940","relation":{},"subject":[],"published":{"date-parts":[[2022,11,10]]},"assertion":[{"value":"2023-03-15","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}