{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,23]],"date-time":"2024-10-23T10:08:46Z","timestamp":1729678126507,"version":"3.28.0"},"reference-count":18,"publisher":"SPIE","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019,3,15]]},"DOI":"10.1117\/12.2511610","type":"proceedings-article","created":{"date-parts":[[2019,3,16]],"date-time":"2019-03-16T09:59:10Z","timestamp":1552730350000},"page":"79","source":"Crossref","is-referenced-by-count":0,"title":["Left ventricle segmentation in LGE-MRI using multiclass learning"],"prefix":"10.1117","author":[{"given":"Tanja","family":"Kurzendorfer","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Katharina","family":"Breininger","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Stefan","family":"Steidl","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Andreas","family":"Maier","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rebecca","family":"Fahrig","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"189","reference":[{"key":"R1","unstructured":"\u201cThe top 10 causes of death.\u201d http:\/\/www.who.int\/en\/news-room\/fact-sheets\/detail\/the-top-10-causes-of-death (May 2018). Accessed: 2018\u201326-07."},{"key":"R2","volume-title":"Taylor\u2019s Cardiovascular Diseases: A Handbook","volume":"79","author":"David","year":"2005"},{"key":"R3","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2013.09.001"},{"key":"R4","doi-asserted-by":"publisher","DOI":"10.1186\/1532-429X-17-S1-Q26"},{"key":"R5","doi-asserted-by":"crossref","unstructured":"Kurzendorfer, T., Forman, C., Brost, A., and Maier, A., \u201cRandom Forest Based Left Ventricle Segmentation in LGE-MRI,\u201d in [International Conference on Functional Imaging and Modeling of the Heart], Pop, M. and Wright, G. A., eds., 152\u2013160, Springer (May 2017).","DOI":"10.1007\/978-3-319-59448-4_15"},{"key":"R6","first-page":"1","article-title":"Myocardium segmentation from DE MRI with guided random walks and sparse shape representation","author":"Liu","year":"2018","journal-title":"International journal of computer assisted radiology and surgery"},{"key":"R7","doi-asserted-by":"publisher","DOI":"10.1002\/jmri.v42.2"},{"key":"R8","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.v72.6"},{"key":"R9","doi-asserted-by":"crossref","DOI":"10.1145\/3194554","article-title":"Automatic multi-organ segmentation in dual energy CT using 3D fully convolutional network","author":"Chen","year":"2018","journal-title":"MIDL 2018"},{"key":"R10","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2018.2837502"},{"key":"R11","first-page":"234","article-title":"U-net: Convolutional networks for biomedical image segmentation","volume-title":"International Conference on Medical image computing and computer-assisted intervention","author":"Ronneberger","year":"2015"},{"key":"R12","doi-asserted-by":"crossref","unstructured":"Milletari, F., Navab, N., and Ahmadi, S.-A., \u201cV-net: Fully convolutional neural networks for volumetric medical image segmentation,\u201d in [3D Vision (3DV), 2016 Fourth International Conference on], 565\u2013571, IEEE (Oct. 2016).","DOI":"10.1109\/3DV.2016.79"},{"key":"R13","article-title":"Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift","author":"Ioffe","year":"2015","journal-title":"arXiv preprint arXiv:1502.03167"},{"key":"R14","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., and Sun, J., \u201cDeep residual learning for image recognition,\u201d in [Proceedings of the IEEE conference on computer vision and pattern recognition], 770\u2013778 (June 2016).","DOI":"10.1109\/CVPR.2016.90"},{"key":"R15","first-page":"1","article-title":"Intraoperative stent segmentation in X-ray fluoroscopy for endovascular aortic repair","author":"Breininger","year":"2018","journal-title":"International journal of computer assisted radiology and surgery"},{"key":"R16","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2005.04.005"},{"key":"R17","doi-asserted-by":"publisher","DOI":"10.1016\/j.ascom.2017.01.002"},{"key":"R18","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-23626-6"}],"event":{"name":"Image Processing","start":{"date-parts":[[2019,2,16]]},"location":"San Diego, United States","end":{"date-parts":[[2019,2,21]]}},"container-title":["Medical Imaging 2019: Image Processing"],"original-title":[],"deposited":{"date-parts":[[2020,12,1]],"date-time":"2020-12-01T05:59:56Z","timestamp":1606802396000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.spiedigitallibrary.org\/conference-proceedings-of-spie\/10949\/2511610\/Left-ventricle-segmentation-in-LGE-MRI-using-multiclass-learning\/10.1117\/12.2511610.full"}},"subtitle":[],"editor":[{"given":"Elsa D.","family":"Angelini","sequence":"additional","affiliation":[],"role":[{"role":"editor","vocabulary":"crossref"}]},{"given":"Bennett A.","family":"Landman","sequence":"additional","affiliation":[],"role":[{"role":"editor","vocabulary":"crossref"}]}],"short-title":[],"issued":{"date-parts":[[2019,3,15]]},"references-count":18,"URL":"https:\/\/doi.org\/10.1117\/12.2511610","relation":{},"subject":[],"published":{"date-parts":[[2019,3,15]]}}}