{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:29:26Z","timestamp":1750220966586,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":19,"publisher":"ACM","license":[{"start":{"date-parts":[[2019,8,24]],"date-time":"2019-08-24T00:00:00Z","timestamp":1566604800000},"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":[[2019,8,24]]},"DOI":"10.1145\/3364836.3364842","type":"proceedings-article","created":{"date-parts":[[2019,12,23]],"date-time":"2019-12-23T13:04:52Z","timestamp":1577106292000},"page":"27-30","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["Convolutional Neural Networks Based Level Set Framework for Pancreas Segmentation from CT Images"],"prefix":"10.1145","author":[{"given":"Zhaoxuan","family":"Gong","sequence":"first","affiliation":[{"name":"Shenyang Aerospace University, Shenyang, Liaoning China and Key Laboratory of Intelligent Computing in Medical Image, Ministry of Education, Shenyang, Liaoning China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhenyu","family":"Zhu","sequence":"additional","affiliation":[{"name":"Shenyang Aerospace University, Shenyang, Liaoning China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guodong","family":"Zhang","sequence":"additional","affiliation":[{"name":"Shenyang Aerospace University, Shenyang, Liaoning China and Key Laboratory of Intelligent Computing in Medical Image, Ministry of Education, Shenyang, Liaoning China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dazhe","family":"Zhao","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Northeastern University, Shenyang, Liaoning, China and Key Laboratory of Intelligent Computing in Medical Image, Ministry of Education, Shenyang, Liaoning China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wei","family":"Guo","sequence":"additional","affiliation":[{"name":"Shenyang Aerospace University, Shenyang, Liaoning China and Key Laboratory of Intelligent Computing in Medical Image, Ministry of Education, Shenyang, Liaoning China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2019,8,24]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1136\/gut.2006.103333"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2016.2624198"},{"key":"e_1_3_2_1_3_1","volume-title":"Yuille. A Fixed-Point Model for Pancreas Segmentation in Abdominal CT Scans. MICCAI 2017","author":"Zhou Yuyin","year":"2017","unstructured":"Yuyin Zhou , Lingxi Xie , Wei Shen , Yan Wang , Elliot K. Fishman , and Alan L . Yuille. A Fixed-Point Model for Pancreas Segmentation in Abdominal CT Scans. MICCAI 2017 ,( 2017 ), 693--701. Yuyin Zhou, Lingxi Xie, Wei Shen, Yan Wang, Elliot K. Fishman, and Alan L. Yuille. A Fixed-Point Model for Pancreas Segmentation in Abdominal CT Scans. MICCAI 2017,(2017), 693--701."},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1155\/2013\/479516","article-title":"A Hybrid Method for Pancreas Extraction from CT Image Based on Level Set Methods","volume":"2013","author":"Jiang Huiyan","year":"2013","unstructured":"Huiyan Jiang , Hanqing Tan , and Hiroshi Fujita . A Hybrid Method for Pancreas Extraction from CT Image Based on Level Set Methods . Computational and Mathematical Methods in Medicine , 2013 ,( 2013 ), 1 -- 13 . Huiyan Jiang, Hanqing Tan, and Hiroshi Fujita. A Hybrid Method for Pancreas Extraction from CT Image Based on Level Set Methods. Computational and Mathematical Methods in Medicine,2013,(2013),1--13.","journal-title":"Computational and Mathematical Methods in Medicine"},{"issue":"2","key":"e_1_3_2_1_5_1","first-page":"3660","article-title":"Automatic Fast Pancreas Segmentation and Classification of Abdominal CT Scans","volume":"6","author":"Adaline Suji Dr. R.","year":"2018","unstructured":"Dr. R. Adaline Suji , V. Santhoshkumar . Automatic Fast Pancreas Segmentation and Classification of Abdominal CT Scans . International Journal for Scientific Research & Development , 6 ( 2 ),( 2018 ), 3660 -- 3666 . Dr. R. Adaline Suji, V. Santhoshkumar. Automatic Fast Pancreas Segmentation and Classification of Abdominal CT Scans. International Journal for Scientific Research & Development, 6(2),(2018),3660--3666.","journal-title":"International Journal for Scientific Research & Development"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"crossref","unstructured":"Karasawa K Oda M Kitasaka T Misawa K Fujiwara M Chu C Zheng G Rueckert D Mori K. Multi-atlas pancreas segmentation: Atlas selection based on vessel structure. 39 (2017) 18--28.  Karasawa K Oda M Kitasaka T Misawa K Fujiwara M Chu C Zheng G Rueckert D Mori K. Multi-atlas pancreas segmentation: Atlas selection based on vessel structure. 39 (2017) 18--28.","DOI":"10.1016\/j.media.2017.03.006"},{"key":"e_1_3_2_1_7_1","volume-title":"MICCIA 2017","author":"Jinzheng","year":"2017","unstructured":"Jinzheng C, Le Lu , Zizhao Zhang , Fuyong Xing , Lin Yang , and Qian Yin . Pancreas Segmentation in MRI using Graph-Based Decision Fusion on Convolutional Neural Networks . MICCIA 2017 ,( 2017 ), 674--682. Jinzheng C, Le Lu, Zizhao Zhang, Fuyong Xing, Lin Yang, and Qian Yin. Pancreas Segmentation in MRI using Graph-Based Decision Fusion on Convolutional Neural Networks. MICCIA 2017,(2017), 674--682."},{"key":"e_1_3_2_1_8_1","volume-title":"Summers","author":"Lu H.R.","year":"2015","unstructured":"Roth, H.R. , Lu , L., Farag, A., Shin, H.C. , Liu , J., Turkbey, E. B. , Summers , R.M. : DeepOrgan: Multi-level Deep Convolutional Networks for Automated Pancreas Segmentation, MICCAI ( 2015 ),556--564. Roth, H.R., Lu, L., Farag, A., Shin, H.C., Liu, J., Turkbey, E.B., Summers, R.M.: DeepOrgan: Multi-level Deep Convolutional Networks for Automated Pancreas Segmentation, MICCAI (2015),556--564."},{"key":"e_1_3_2_1_9_1","volume-title":"Summers","author":"Lu H.R.","year":"2016","unstructured":"Roth, H.R. , Lu , L., Farag, A., Sohn, A. , Summers , R.M. : Spatial Aggregation of Holistically-Nested Networks for Automated Pancreas Segmentation,. Medical Image Computing and Computer-Assisted Intervention ( 2016 ), 451--450. Roth, H.R., Lu, L., Farag, A., Sohn, A., Summers, R.M.: Spatial Aggregation of Holistically-Nested Networks for Automated Pancreas Segmentation,. Medical Image Computing and Computer-Assisted Intervention (2016), 451--450."},{"key":"e_1_3_2_1_10_1","volume-title":"CVPR2017","author":"Lu H.R.","year":"2017","unstructured":"Roth, H.R. , Lu , L., Lay, N., Harrison, A.P. , Farag , A., Summers, R. M. : Spatial aggregation of holistically-nested convolutional neural networks for automated pancreas localization and segmentation . CVPR2017 , ( 2017 ). Roth, H.R., Lu, L., Lay, N., Harrison, A.P., Farag, A., Summers, R.M.: Spatial aggregation of holistically-nested convolutional neural networks for automated pancreas localization and segmentation. CVPR2017, (2017)."},{"key":"e_1_3_2_1_11_1","volume-title":"CVPR2007","author":"Chunming","year":"2007","unstructured":"Chunming L, Chiu-Yen Kao , John C. Gore , Zhaohua Ding . Implicit Active Contours Driven by Local Binary Fitting Energy . CVPR2007 , ( 2007 ). Chunming L,Chiu-Yen Kao,John C. Gore, Zhaohua Ding. Implicit Active Contours Driven by Local Binary Fitting Energy. CVPR2007, (2007)."},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2008.2002304"},{"key":"e_1_3_2_1_13_1","volume-title":"Fox. Level Set Evolution Without Re-initialization: A New Variational Formulation. CVPR2005","author":"Chunming","year":"2005","unstructured":"Chunming L, Chenyang X, Changfeng G, and Martin D . Fox. Level Set Evolution Without Re-initialization: A New Variational Formulation. CVPR2005 , ( 2005 ). Chunming L, Chenyang X, Changfeng G, and Martin D. Fox. Level Set Evolution Without Re-initialization: A New Variational Formulation. CVPR2005, (2005)."},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1109\/83.902291"},{"issue":"118","key":"e_1_3_2_1_15_1","first-page":"203","article-title":"An Approach to Extraction Midsagittal Plane of Skull From Bra","volume":"7","author":"Wenjun","year":"2019","unstructured":"Wenjun T, Ying K, Zhiwei D et al. An Approach to Extraction Midsagittal Plane of Skull From Bra in CT Images for Oral and Maxillofacial Surgery. IEEE Access , 7 ( 118 ),( 2019 ), 203 -- 217 . Wenjun T, Ying K, Zhiwei D et al. An Approach to Extraction Midsagittal Plane of Skull From Brain CT Images for Oral and Maxillofacial Surgery. IEEE Access,7(118),(2019),203--217.","journal-title":"CT Images for Oral and Maxillofacial Surgery. IEEE Access"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"crossref","unstructured":"O. Ronneberger P. Fischer and T. Brox \"U-net: Convolutional networks for biomedical image segmentation \" in International Conference on Medical Image Computing and Computer Assisted Intervention (2015) 234--241.  O. Ronneberger P. Fischer and T. Brox \"U-net: Convolutional networks for biomedical image segmentation \" in International Conference on Medical Image Computing and Computer Assisted Intervention (2015) 234--241.","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1088\/0031-8949\/43\/2\/011"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2010.2069690"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.imavis.2009.10.009"}],"event":{"name":"ISICDM 2019: The Third International Symposium on Image Computing and Digital Medicine","sponsor":["Xidian University"],"location":"Xi'an China","acronym":"ISICDM 2019"},"container-title":["Proceedings of the Third International Symposium on Image Computing and Digital Medicine"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3364836.3364842","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3364836.3364842","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T23:54:22Z","timestamp":1750204462000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3364836.3364842"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,8,24]]},"references-count":19,"alternative-id":["10.1145\/3364836.3364842","10.1145\/3364836"],"URL":"https:\/\/doi.org\/10.1145\/3364836.3364842","relation":{},"subject":[],"published":{"date-parts":[[2019,8,24]]},"assertion":[{"value":"2019-08-24","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}