{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,23]],"date-time":"2025-08-23T00:05:42Z","timestamp":1755907542075,"version":"3.44.0"},"publisher-location":"New York, NY, USA","reference-count":14,"publisher":"ACM","license":[{"start":{"date-parts":[[2022,10,13]],"date-time":"2022-10-13T00:00:00Z","timestamp":1665619200000},"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":[[2022,10,13]]},"DOI":"10.1145\/3570773.3570818","type":"proceedings-article","created":{"date-parts":[[2022,12,9]],"date-time":"2022-12-09T15:57:42Z","timestamp":1670601462000},"page":"76-80","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Intelligent Diagnosis of Vascular Anomalies with Deep Learning"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5257-2583","authenticated-orcid":false,"given":"Yuwei","family":"Cai","sequence":"first","affiliation":[{"name":"School of Artificial Intelligence, JiangHan University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1928-2522","authenticated-orcid":false,"given":"Xia","family":"Gong","sequence":"additional","affiliation":[{"name":"Department of Ultrasound, Shanghai 9th People' Hospital, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7242-0376","authenticated-orcid":false,"given":"Qiang","family":"He","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, JiangHan University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8117-4541","authenticated-orcid":false,"given":"Xindong","family":"Fan","sequence":"additional","affiliation":[{"name":"Intervention Department of the Hospital, Shanghai 9th People' Hospital, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8755-6815","authenticated-orcid":false,"given":"Ping","family":"Xiong","sequence":"additional","affiliation":[{"name":"Department of Ultrasound, Shanghai 9th People' Hospital, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2022,12,9]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.bjoms.2015.09.005"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1148\/radiographics.21.6.g01nv031519"},{"key":"e_1_3_2_1_3_1","first-page":"632","volume":"2016","author":"Ma Yuan","unstructured":"Ma Yuan, Xiong Ping, Gong Xia, Differential Diagnosis Study in Deep Infantile Hemangioma and Pediatric Venous Malformations By Ultrasonography[J]. Chinese J Ultrasound Med,2016,32(07):632-634.","journal-title":"Chinese J Ultrasound Med"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jvsv.2019.01.065"},{"key":"e_1_3_2_1_5_1","volume-title":"Fully convolutional networks for semantic segmentation [J]","author":"Shelhamer E","year":"2016","unstructured":"Shelhamer E, Long J, Darrell T. Fully convolutional networks for semantic segmentation [J]. IEEE transactions on pattern analysis and machine intelligence, 2016, 39(4): 640-651"},{"key":"e_1_3_2_1_6_1","volume-title":"Brox T. U-net: Convolutional networks for biomedical image segmentation[C]\/\/International Conference on Medical image computing and computer-assisted intervention","author":"Ronneberger O","year":"2015","unstructured":"Ronneberger O, Fischer P, Brox T. U-net: Convolutional networks for biomedical image segmentation[C]\/\/International Conference on Medical image computing and computer-assisted intervention. Springer, Cham, 2015: 234-241."},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2020.05.070"},{"key":"e_1_3_2_1_8_1","volume-title":"Ahmadi S A. V-net: Fully convolutional neural networks for volumetric medical image segmentation[C]\/\/2016 fourth international conference on 3D vision (3DV)","author":"Milletari F","year":"2016","unstructured":"Milletari F, Navab N, Ahmadi S A. V-net: Fully convolutional neural networks for volumetric medical image segmentation[C]\/\/2016 fourth international conference on 3D vision (3DV). IEEE, 2016: 565-571."},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2019.01.055"},{"key":"e_1_3_2_1_10_1","volume-title":"Automatic liver segmentation using an adversarial image-to-image network[C]\/\/International conference on medical image computing and computer-assisted intervention","author":"Yang D","year":"2017","unstructured":"Yang D, Xu D, Zhou S K, Automatic liver segmentation using an adversarial image-to-image network[C]\/\/International conference on medical image computing and computer-assisted intervention. Springer, Cham, 2017: 507-515."},{"key":"e_1_3_2_1_11_1","volume-title":"Very deep convolutional networks for large-scale image recognition[J]. arXiv preprint arXiv:1409.1556","author":"Simonyan K","year":"2014","unstructured":"Simonyan K, Zisserman A. Very deep convolutional networks for large-scale image recognition[J]. arXiv preprint arXiv:1409.1556, 2014."},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2962617"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"crossref","unstructured":"Chen X Williams B M Vallabhaneni S R Learning active contour models for medical image segmentation[C]\/\/Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition. 2019: 11632-11640.","DOI":"10.1109\/CVPR.2019.01190"},{"key":"e_1_3_2_1_14_1","volume-title":"Deep Learning","author":"Ian Goodfellow","year":"2016","unstructured":"Ian Goodfellow, Yoshua Bengio, Aaron Courville. Deep Learning. MIT Press 2016."}],"event":{"name":"ISAIMS 2022: 2022 3rd International Symposium on Artificial Intelligence for Medicine Sciences","acronym":"ISAIMS 2022","location":"Amsterdam Netherlands"},"container-title":["Proceedings of the 3rd International Symposium on Artificial Intelligence for Medicine Sciences"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3570773.3570818","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3570773.3570818","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T06:48:46Z","timestamp":1755845326000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3570773.3570818"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,10,13]]},"references-count":14,"alternative-id":["10.1145\/3570773.3570818","10.1145\/3570773"],"URL":"https:\/\/doi.org\/10.1145\/3570773.3570818","relation":{},"subject":[],"published":{"date-parts":[[2022,10,13]]},"assertion":[{"value":"2022-12-09","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}