{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T14:40:06Z","timestamp":1755873606268,"version":"3.44.0"},"publisher-location":"New York, NY, USA","reference-count":31,"publisher":"ACM","license":[{"start":{"date-parts":[[2023,10,20]],"date-time":"2023-10-20T00:00:00Z","timestamp":1697760000000},"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":[[2023,10,20]]},"DOI":"10.1145\/3644116.3644125","type":"proceedings-article","created":{"date-parts":[[2024,4,5]],"date-time":"2024-04-05T18:38:22Z","timestamp":1712342302000},"page":"35-39","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Cascaded Multi-scale Attention Network for Automatic Segmentation of the Right Ventricle in Cardiac Magnetic Resonance"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-2460-7526","authenticated-orcid":false,"given":"Yuetong","family":"Lu","sequence":"first","affiliation":[{"name":"Guangdong University of Technology, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-1278-3044","authenticated-orcid":false,"given":"Liangkun","family":"Fang","sequence":"additional","affiliation":[{"name":"Zhejiang Sci-Tech University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2024,4,5]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMra2115011"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1093\/eurheartj\/ehab892"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.chest.2020.09.274"},{"key":"e_1_3_2_1_4_1","first-page":"241","volume-title":"Brox","author":"Ronneberger O.","year":"2015","unstructured":"O. Ronneberger, P. Fischer, T. Brox, U-net: Convolutional networks for biomedical image segmentation, in: Int. Conf. Med. Image Comput. Comput. Interv., Springer, 2015: pp. 234\u2013241."},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-00889-5_1"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2020.2996645"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMra2115011"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1093\/eurheartj\/ehab892"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.chest.2020.09.274"},{"key":"e_1_3_2_1_10_1","first-page":"241","volume-title":"Brox","author":"Ronneberger O.","year":"2015","unstructured":"O. Ronneberger, P. Fischer, T. Brox, U-net: Convolutional networks for biomedical image segmentation, in: Int. Conf. Med. Image Comput. Comput. Interv., Springer, 2015: pp. 234\u2013241."},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-00889-5_1"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2020.2996645"},{"key":"e_1_3_2_1_13_1","first-page":"4","volume-title":"Culurciello","author":"Chaurasia A.","year":"2017","unstructured":"A. Chaurasia, E. Culurciello, Linknet: Exploiting encoder representations for efficient semantic segmentation, in: 2017 IEEE Vis. Commun. Image Process., IEEE, 2017: pp. 1\u20134."},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2016.2644615"},{"key":"e_1_3_2_1_15_1","first-page":"62","article-title":"Peng, A deep segmentation network of multi-scale feature fusion based on attention mechanism for IVOCT lumen contour","author":"Huang C.","year":"2020","unstructured":"C. Huang, Y. Lan, G. Xu, X. Zhai, J. Wu, F. Lin, N. Zeng, Q. Hong, E.Y.K. Ng, Y. Peng, A deep segmentation network of multi-scale feature fusion based on attention mechanism for IVOCT lumen contour, IEEE\/ACM Trans. Comput. Biol. Bioinforma. 18. 2020. 62\u201369.","journal-title":"IEEE\/ACM Trans. Comput. Biol. Bioinforma. 18."},{"key":"e_1_3_2_1_16_1","first-page":"121","article-title":"Dolz, Multi-scale self-guided attention for medical image segmentation","author":"Sinha A.","year":"2020","unstructured":"A. Sinha, J. Dolz, Multi-scale self-guided attention for medical image segmentation, IEEE J. Biomed. Heal. Informatics. 25. 2020. 121\u2013130.","journal-title":"IEEE J. Biomed. Heal. Informatics. 25."},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2020.3015224"},{"key":"e_1_3_2_1_18_1","first-page":"101891","author":"Wu H.","year":"2020","unstructured":"H. Wu, X. Lu, B. Lei, Z. Wen, Automated Left Ventricular Segmentation from Cardiac Magnetic Resonance Images via Adversarial Learning with Multi-stage Pose Estimation Network and Co-discriminator, Med. Image Anal. 2020. 101891.","journal-title":"Med. Image Anal."},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2021.102205"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2020.101766"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"crossref","unstructured":"Z. Wu R. Ge M. Wen G. Liu Y. Chen P. Zhang X. He J. Hua L. Luo S. Li ELNet: Automatic Classification and Segmentation for Esophageal Lesions using Convolutional Neural Network Med. Image Anal. 2020 101838.","DOI":"10.1016\/j.media.2020.101838"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-32248-9_47"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-32245-8_60"},{"key":"e_1_3_2_1_24_1","first-page":"2105","author":"You C.","year":"2021","unstructured":"C. You, R. Zhao, L. Staib, J.S. Duncan, Momentum Contrastive Voxel-wise Representation Learning for Semi-supervised Volumetric Medical Image Segmentation, ArXiv E-Prints. 2021. arXiv:2105.07059. https:\/\/ui.adsabs.harvard.edu\/abs\/2021arXiv210507059Y.","journal-title":"ArXiv E-Prints."},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2020.101753"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2019.2901750"},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1002\/mp.12155"},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01234-2_1"},{"volume-title":"Proc. IEEE Conf. Comput. Vis. Pattern Recognit., IEEE","author":"Li W.","key":"e_1_3_2_1_29_1","unstructured":"W. Li, X. Zhu, S. Gong, Harmonious attention network for person re-identification, in: Proc. IEEE Conf. Comput. Vis. Pattern Recognit., IEEE, 2018: pp. 2285\u20132294."},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1002\/jmri.27881"},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1093\/ehjci\/jeac037"}],"event":{"name":"ISAIMS 2023: 2023 4th International Symposium on Artificial Intelligence for Medicine Science","acronym":"ISAIMS 2023","location":"Chengdu China"},"container-title":["Proceedings of the 2023 4th International Symposium on Artificial Intelligence for Medicine Science"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3644116.3644125","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3644116.3644125","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T14:04:43Z","timestamp":1755871483000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3644116.3644125"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,10,20]]},"references-count":31,"alternative-id":["10.1145\/3644116.3644125","10.1145\/3644116"],"URL":"https:\/\/doi.org\/10.1145\/3644116.3644125","relation":{},"subject":[],"published":{"date-parts":[[2023,10,20]]},"assertion":[{"value":"2024-04-05","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}