{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,4,28]],"date-time":"2025-04-28T05:40:07Z","timestamp":1745818807069,"version":"3.40.4"},"publisher-location":"Cham","reference-count":27,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031877551","type":"print"},{"value":"9783031877568","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025]]},"DOI":"10.1007\/978-3-031-87756-8_35","type":"book-chapter","created":{"date-parts":[[2025,4,28]],"date-time":"2025-04-28T05:08:59Z","timestamp":1745816939000},"page":"357-367","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["ResNet-Based Convolutional Framework for\u00a0Segmenting Left Atrial Scars and\u00a0Cavities"],"prefix":"10.1007","author":[{"given":"Malitha","family":"Gunawardhana","sequence":"first","affiliation":[]},{"given":"Fangqiang","family":"Xu","sequence":"additional","affiliation":[]},{"given":"Yun","family":"Gu","sequence":"additional","affiliation":[]},{"given":"Jichao","family":"Zhao","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,4,29]]},"reference":[{"issue":"10","key":"35_CR1","doi-asserted-by":"publisher","first-page":"1104","DOI":"10.1111\/jce.12199","volume":"24","author":"N Akoum","year":"2013","unstructured":"Akoum, N., Fernandez, G., Wilson, B., Mcgann, C., Kholmovski, E., Marrouche, N.: Association of atrial fibrosis quantified using LGE-MRI with atrial appendage thrombus and spontaneous contrast on transesophageal echocardiography in patients with atrial fibrillation. J. Cardiovasc. Electrophysiol. 24(10), 1104\u20131109 (2013)","journal-title":"J. Cardiovasc. Electrophysiol."},{"key":"35_CR2","unstructured":"Gunawardhana, M., Kulathilaka, A., Zhao, J.: Integrating deep learning in cardiology: a comprehensive review of atrial fibrillation, left atrial scar segmentation, and the frontiers of state-of-the-art techniques. arXiv preprint (2024). arXiv:2407.09561"},{"key":"35_CR3","doi-asserted-by":"crossref","unstructured":"Gunawardhana, M., Xu, F., Zhao, J.: How good nnU-Net for segmenting cardiac MRI: a comprehensive evaluation. Res. Square (2024)","DOI":"10.21203\/rs.3.rs-4786465\/v1"},{"key":"35_CR4","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 770\u2013778 (2016)","DOI":"10.1109\/CVPR.2016.90"},{"issue":"2","key":"35_CR5","doi-asserted-by":"publisher","first-page":"203","DOI":"10.1038\/s41592-020-01008-z","volume":"18","author":"F Isensee","year":"2021","unstructured":"Isensee, F., Jaeger, P.F., Kohl, S.A., Petersen, J., Maier-Hein, K.H.: nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation. Nat. Methods 18(2), 203\u2013211 (2021)","journal-title":"Nat. Methods"},{"key":"35_CR6","doi-asserted-by":"crossref","unstructured":"Isensee, F., et al.: nnU-Net revisited: a call for rigorous validation in 3D medical image segmentation. arXiv preprint (2024). arXiv:2404.09556","DOI":"10.1007\/978-3-031-72114-4_47"},{"key":"35_CR7","doi-asserted-by":"crossref","unstructured":"Jiang, L., Li, Y., Wang, Y., Cui, H., Xia, Y., Zhang, Y.: Deep u-net architecture with curriculum learning for left atrial segmentation. In: Challenge on Left Atrial and Scar Quantification and Segmentation, pp. 115\u2013123. Springer (2022)","DOI":"10.1007\/978-3-031-31778-1_11"},{"key":"35_CR8","doi-asserted-by":"crossref","unstructured":"Jin, D., Xu, Z., Harrison, A.P., Mollura, D.J.: White matter hyperintensity segmentation from T1 and FLAIR images using fully convolutional neural networks enhanced with residual connections. In: 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018), pp. 1060\u20131064. IEEE (2018)","DOI":"10.1109\/ISBI.2018.8363754"},{"issue":"1","key":"35_CR9","doi-asserted-by":"publisher","first-page":"105","DOI":"10.1186\/1532-429X-15-105","volume":"15","author":"R Karim","year":"2013","unstructured":"Karim, R., et al.: Evaluation of current algorithms for segmentation of scar tissue from late gadolinium enhancement cardiovascular magnetic resonance of the left atrium: an open-access grand challenge. J. Cardiovasc. Magn. Reson. 15(1), 105 (2013)","journal-title":"J. Cardiovasc. Magn. Reson."},{"key":"35_CR10","doi-asserted-by":"crossref","unstructured":"Khan, A., Alwazzan, O., Benning, M., Slabaugh, G.: Sequential segmentation of the left atrium and atrial scars using a multi-scale weight sharing network and boundary-based processing. In: Challenge on Left Atrial and Scar Quantification and Segmentation, pp. 69\u201382. Springer, Cham (2022)","DOI":"10.1007\/978-3-031-31778-1_7"},{"issue":"3","key":"35_CR11","doi-asserted-by":"publisher","first-page":"1314","DOI":"10.1016\/j.bbe.2020.07.007","volume":"40","author":"A Khanna","year":"2020","unstructured":"Khanna, A., Londhe, N.D., Gupta, S., Semwal, A.: A deep residual U-net convolutional neural network for automated lung segmentation in computed tomography images. Biocybern. Biomed. Eng. 40(3), 1314\u20131327 (2020)","journal-title":"Biocybern. Biomed. Eng."},{"key":"35_CR12","doi-asserted-by":"crossref","unstructured":"Lefebvre, A.L., et al.: LASSNet: a four steps deep neural network for left atrial segmentation and scar quantification. In: Challenge on Left Atrial and Scar Quantification and Segmentation, pp. 1\u201315 (2022)","DOI":"10.1007\/978-3-031-31778-1_1"},{"key":"35_CR13","doi-asserted-by":"crossref","unstructured":"Li, F., Li, W.: Cross-domain segmentation of left atrium based on multi-scale decision level fusion. In: Challenge on Left Atrial and Scar Quantification and Segmentation, pp. 124\u2013132. Springer, Cham (2022)","DOI":"10.1007\/978-3-031-31778-1_12"},{"key":"35_CR14","doi-asserted-by":"crossref","unstructured":"Linz, D., et al.: Atrial fibrillation: epidemiology, screening and digital health. Lancet Reg. Health\u2013Eur. 37 (2024)","DOI":"10.1016\/j.lanepe.2023.100786"},{"key":"35_CR15","doi-asserted-by":"crossref","unstructured":"Liu, T., Hou, S., Zhu, J., Zhao, Z., Jiang, H.: Ugformer for robust left atrium and scar segmentation across scanners. In: Challenge on Left Atrial and Scar Quantification and Segmentation, pp. 36\u201348. Springer, Cham (2022)","DOI":"10.1007\/978-3-031-31778-1_4"},{"key":"35_CR16","doi-asserted-by":"publisher","first-page":"102035","DOI":"10.1016\/j.media.2021.102035","volume":"71","author":"J Ma","year":"2021","unstructured":"Ma, J., et al.: Loss odyssey in medical image segmentation. Med. Image Anal. 71, 102035 (2021)","journal-title":"Med. Image Anal."},{"issue":"5","key":"35_CR17","doi-asserted-by":"publisher","first-page":"498","DOI":"10.1001\/jama.2014.3","volume":"311","author":"NF Marrouche","year":"2014","unstructured":"Marrouche, N.F., et al.: Association of atrial tissue fibrosis identified by delayed enhancement MRI and atrial fibrillation catheter ablation: the DECAAF study. JAMA 311(5), 498\u2013506 (2014)","journal-title":"JAMA"},{"key":"35_CR18","doi-asserted-by":"crossref","unstructured":"Mazher, M., Qayyum, A., Abdel-Nasser, M., Puig, D.: Automatic semi-supervised left atrial segmentation using deep-supervision 3dresunet with pseudo labeling approach for lascarqs 2022 challenge. In: Challenge on Left Atrial and Scar Quantification and Segmentation, pp. 153\u2013161. Springer, Cham (2022)","DOI":"10.1007\/978-3-031-31778-1_15"},{"key":"35_CR19","doi-asserted-by":"crossref","unstructured":"Punithakumar, K., Noga, M.: Automated segmentation of the left atrium and scar using deep convolutional neural networks. In: Challenge on Left Atrial and Scar Quantification and Segmentation, pp. 145\u2013152. Springer, Cham (2022)","DOI":"10.1007\/978-3-031-31778-1_14"},{"key":"35_CR20","doi-asserted-by":"publisher","first-page":"105177","DOI":"10.1016\/j.bspc.2023.105177","volume":"86","author":"KR Singh","year":"2023","unstructured":"Singh, K.R., Sharma, A., Singh, G.K.: Attention-guided residual W-net for supervised cardiac magnetic resonance imaging segmentation. Biomed. Signal Process. Control 86, 105177 (2023)","journal-title":"Biomed. Signal Process. Control"},{"key":"35_CR21","first-page":"1","volume":"73","author":"KR Singh","year":"2023","unstructured":"Singh, K.R., Sharma, A., Singh, G.K.: MADRU-Net: multi-scale attention-based cardiac MRI segmentation using deep residual U-net. IEEE Trans. Instrum. Measur. 73, 1\u201313 (2023)","journal-title":"IEEE Trans. Instrum. Measur."},{"key":"35_CR22","first-page":"749","volume":"38","author":"D Stalling","year":"2005","unstructured":"Stalling, D., Westerhoff, M., Hege, H.C.: Amira: a highly interactive system for visual data analysis. Vis. Handb. 38, 749\u2013767 (2005)","journal-title":"Vis. Handb."},{"key":"35_CR23","doi-asserted-by":"crossref","unstructured":"Tu, C., et al.: Self pre-training with single-scale adapter for left atrial segmentation. In: Challenge on Left Atrial and Scar Quantification and Segmentation, pp. 24\u201335. Springer, Cham (2022)","DOI":"10.1007\/978-3-031-31778-1_3"},{"key":"35_CR24","doi-asserted-by":"publisher","first-page":"101832","DOI":"10.1016\/j.media.2020.101832","volume":"67","author":"Z Xiong","year":"2021","unstructured":"Xiong, Z., et al.: A global benchmark of algorithms for segmenting the left atrium from late gadolinium-enhanced cardiac magnetic resonance imaging. Med. Image Anal. 67, 101832 (2021)","journal-title":"Med. Image Anal."},{"key":"35_CR25","doi-asserted-by":"crossref","unstructured":"Yushkevich, P.A., Gao, Y., Gerig, G.: ITK-SNAP: an interactive tool for semi-automatic segmentation of multi-modality biomedical images. In: 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 3342\u20133345. IEEE (2016)","DOI":"10.1109\/EMBC.2016.7591443"},{"key":"35_CR26","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Meng, Y., Zheng, Y.: Automatically segment the left atrium and scars from LGE-MRIs using a boundary-focused nnU-Net. In: Challenge on Left Atrial and Scar Quantification and Segmentation, pp. 49\u201359. Springer, Cham (2022)","DOI":"10.1007\/978-3-031-31778-1_5"},{"key":"35_CR27","doi-asserted-by":"crossref","unstructured":"Zhuang, X.: Left atrial and scar quantification and segmentation: first challenge. In: LAScarQS 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18, 2022, Proceedings. Springer Nature (2023)","DOI":"10.1007\/978-3-031-31778-1"}],"container-title":["Lecture Notes in Computer Science","Statistical Atlases and Computational Models of the Heart. Workshop, CMRxRecon and MBAS Challenge Papers."],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-87756-8_35","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,4,28]],"date-time":"2025-04-28T05:09:14Z","timestamp":1745816954000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-87756-8_35"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9783031877551","9783031877568"],"references-count":27,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-87756-8_35","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"29 April 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"STACOM","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Workshop on Statistical Atlases and Computational Models of the Heart","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Marrakesh","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Morocco","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"9 October 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"9 October 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"stacom2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/stacom.github.io\/stacom2024\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}