{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,15]],"date-time":"2025-11-15T10:28:54Z","timestamp":1763202534776,"version":"3.41.0"},"reference-count":30,"publisher":"Association for Computing Machinery (ACM)","issue":"12","license":[{"start":{"date-parts":[[2021,11,19]],"date-time":"2021-11-19T00:00:00Z","timestamp":1637280000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/501100012245","name":"Science and Technology Planning Project of Guangdong Province","doi-asserted-by":"crossref","award":["2017B090904034;2017B030314109; 2018B090944002; 2019B020230003"],"award-info":[{"award-number":["2017B090904034;2017B030314109; 2018B090944002; 2019B020230003"]}],"id":[{"id":"10.13039\/501100012245","id-type":"DOI","asserted-by":"crossref"}]},{"name":"National key Research and Development Program of China","award":["2018YFC1002600"],"award-info":[{"award-number":["2018YFC1002600"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["62006050"],"award-info":[{"award-number":["62006050"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Guangdong Peak Project","award":["201802"],"award-info":[{"award-number":["201802"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["Commun. ACM"],"published-print":{"date-parts":[[2021,12]]},"abstract":"<jats:p>3D heart modeling and AI bring new cardiac surgery to remote and less-developed regions.<\/jats:p>","DOI":"10.1145\/3450409","type":"journal-article","created":{"date-parts":[[2021,11,19]],"date-time":"2021-11-19T15:30:18Z","timestamp":1637335818000},"page":"66-74","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":8,"title":["AI-CHD"],"prefix":"10.1145","volume":"64","author":[{"given":"Xiaowei","family":"Xu","sequence":"first","affiliation":[{"name":"Guangdong Provincial People's Hospital"}]},{"given":"Hailong","family":"Qiu","sequence":"additional","affiliation":[{"name":"Guangdong Provincial People's Hospital"}]},{"given":"Qianjun","family":"Jia","sequence":"additional","affiliation":[{"name":"Guangdong Provincial People's Hospital"}]},{"given":"Yuhao","family":"Dong","sequence":"additional","affiliation":[]},{"given":"Zeyang","family":"Yao","sequence":"additional","affiliation":[{"name":"Guangdong Provincial People's Hospital"}]},{"given":"Wen","family":"Xie","sequence":"additional","affiliation":[{"name":"Guangdong Provincial People's Hospital"}]},{"given":"Huiming","family":"Guo","sequence":"additional","affiliation":[{"name":"Guangdong Provincial People's Hospital"}]},{"given":"Haiyun","family":"Yuan","sequence":"additional","affiliation":[{"name":"Guangdong Provincial People's Hospital"}]},{"given":"Jian","family":"Zhuang","sequence":"additional","affiliation":[{"name":"Guangdong Provincial People's Hospital"}]},{"given":"Meiping","family":"Huang","sequence":"additional","affiliation":[{"name":"Guangdong Provincial People's Hospital"}]},{"given":"Yiyu","family":"Shi","sequence":"additional","affiliation":[{"name":"University of Notre Dame"}]}],"member":"320","published-online":{"date-parts":[[2021,11,19]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1053\/j.pcsu.2010.02.005"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.4253\/wjge.v6.i5.148"},{"volume-title":"2020 IEEE 17th Intern. Symp. on Biomedical Imaging (ISBI), 862--866","author":"Chen Y-J.","key":"e_1_2_1_3_1","unstructured":"Chen, Y-J., Chang, Y-J., Wen, S-C., Shi, Y., Xu, X., Ho, T-Y., Jia, Q., Huang, M., and Zhuang, J. Zero-shot medical image artifact reduction. In 2020 IEEE 17th Intern. Symp. on Biomedical Imaging (ISBI), 862--866."},{"key":"e_1_2_1_4_1","volume-title":"The Times of India (June 11","author":"Chinese","year":"2019","unstructured":"Chinese surgeons conduct remote surgery using 5G technology. The Times of India (June 11, 2019), https:\/\/timesofindia.indiatimes.com\/world\/china\/chinese-surgeons-conduct-remote-surgery-using-5g-technology\/articleshow\/69742530.cms."},{"key":"e_1_2_1_5_1","volume-title":"Intern. Conf. on Medical Image Computing and Computer-Assisted Intervention. Springer","author":"\u00c7i\u00e7ek","year":"2016","unstructured":"\u00c7i\u00e7ek, \u00d6., Abdulkadir, A., Lienkamp, S.S., Brox, T., and Ronneberger, O. 3D U-Net: Learning dense volumetric segmentation from sparse annotation. In Intern. Conf. on Medical Image Computing and Computer-Assisted Intervention. Springer (2016), 424--432."},{"key":"e_1_2_1_6_1","volume-title":"Independent (Jan. 17","author":"Cuthbertson A.","year":"2019","unstructured":"Cuthbertson, A. Surgeon performs world's first remote operation using 5G surgery on animal in China. Independent (Jan. 17, 2019), https:\/\/www.independent.co.uk\/life-style\/gadgets-and-tech\/news\/5g-surgery-china-robotic-operation-a8732861.html."},{"key":"e_1_2_1_7_1","unstructured":"First AI+5G surgery completed with Huawei's technological support. Global Times (2019) http:\/\/www.globaltimes.cn\/content\/1144600.shtml."},{"key":"e_1_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.amjsurg.2019.07.018"},{"key":"e_1_2_1_9_1","doi-asserted-by":"crossref","unstructured":"Kang E. Koo H.J. Yang D.H. Seo J.B. and Ye J.C. Cycle consistent adversarial denoising network for multiphase coronary CT angiography. (2018) arXiv preprint arXiv:1806.09748.","DOI":"10.1002\/mp.13284"},{"key":"e_1_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0178963"},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1002\/bjs.11364"},{"key":"e_1_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2013.2266257"},{"key":"e_1_2_1_13_1","first-page":"6","article-title":"The ZEUS robotic system: Experimental and clinical applications","volume":"83","author":"Marescaux J.","year":"2003","unstructured":"Marescaux, J. and Rubino, F. The ZEUS robotic system: Experimental and clinical applications. Surgical Clinics 83, 6 (2003), 1305--1315.","journal-title":"Surgical Clinics"},{"key":"e_1_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0003-4975(02)04554-X"},{"key":"e_1_2_1_15_1","volume-title":"World's first 5G-powered surgery: Dr. Antonio de Lacy","author":"Nita R.","year":"2019","unstructured":"Nita, R. World's first 5G-powered surgery: Dr. Antonio de Lacy. World Record Academy (2019), https:\/\/www.worldrecordacademy.org\/medical\/worlds-first-5g-powered-surgery-dr-antonio-de-lacy-219142."},{"key":"e_1_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijcard.2016.05.046"},{"key":"e_1_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-00889-5_38"},{"key":"e_1_2_1_18_1","volume-title":"Intern. Workshop on Statistical Atlases and Computational Models of the Heart. Springer","author":"Payer C.","year":"2017","unstructured":"Payer, C., \u0160tern, D., Bischof, H., and Urschler, M. Multi-label whole heart segmentation using CNNs and anatomical label configurations. In Intern. Workshop on Statistical Atlases and Computational Models of the Heart. Springer (2017), 190--198."},{"key":"e_1_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"e_1_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.4103\/psychiatry.IndianJPsychiatry_211_18"},{"key":"e_1_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jacc.2011.08.025"},{"key":"e_1_2_1_22_1","doi-asserted-by":"crossref","unstructured":"Wang C. MacGillivray T. Macnaught G. Yang G. and Newby D. A two-stage 3D Unet framework for multi-class segmentation on full resolution image. (2018) arXiv preprint arXiv:1804.04341.","DOI":"10.1007\/978-3-030-12029-0_21"},{"key":"e_1_2_1_23_1","volume-title":"Reconstruction, Segmentation, and Analysis of Medical Images","author":"Wolterink J.M.","year":"2016","unstructured":"Wolterink, J.M., Leiner, T., Viergever, M.A., and I\u0161gum, I. Dilated convolutional neural networks for cardiovascular MR segmentation in congenital heart disease. In Reconstruction, Segmentation, and Analysis of Medical Images. Springer (2016), 95--102."},{"key":"e_1_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2017.2708987"},{"key":"e_1_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00866"},{"key":"e_1_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-32245-8_53"},{"key":"e_1_2_1_27_1","volume-title":"5G remote surgery conducted in central China. Xinhua","author":"Yamei","year":"2019","unstructured":"Yamei. 5G remote surgery conducted in central China. Xinhua (2019), http:\/\/www.xinhuanet.com\/english\/2019-06\/11\/c_138134223.htm."},{"key":"e_1_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2018.2827462"},{"key":"e_1_2_1_29_1","volume-title":"Reconstruction, Segmentation, and Analysis of Medical Images","author":"Yu L.","year":"2016","unstructured":"Yu, L., Yang, X., Qin, J., and Heng, P-A. 3D FractalNet: Dense volumetric segmentation for cardiovascular MRI volumes. In Reconstruction, Segmentation, and Analysis of Medical Images. Springer (2016), 103--110."},{"volume-title":"Computer Vision and Pattern Recognition (CVPR), 2011 IEEE Conference, 977--984","author":"Zontak M.","key":"e_1_2_1_30_1","unstructured":"Zontak, M. and Irani, M. Internal statistics of a single natural image. In Computer Vision and Pattern Recognition (CVPR), 2011 IEEE Conference, 977--984."}],"container-title":["Communications of the ACM"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3450409","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3450409","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T20:18:44Z","timestamp":1750191524000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3450409"}},"subtitle":["an AI-based framework for cost-effective surgical telementoring of congenital heart disease"],"short-title":[],"issued":{"date-parts":[[2021,11,19]]},"references-count":30,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2021,12]]}},"alternative-id":["10.1145\/3450409"],"URL":"https:\/\/doi.org\/10.1145\/3450409","relation":{},"ISSN":["0001-0782","1557-7317"],"issn-type":[{"type":"print","value":"0001-0782"},{"type":"electronic","value":"1557-7317"}],"subject":[],"published":{"date-parts":[[2021,11,19]]},"assertion":[{"value":"2021-11-19","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}