{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T11:06:51Z","timestamp":1742987211532,"version":"3.40.3"},"publisher-location":"Cham","reference-count":27,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319598758"},{"type":"electronic","value":"9783319598765"}],"license":[{"start":{"date-parts":[[2017,1,1]],"date-time":"2017-01-01T00:00:00Z","timestamp":1483228800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2017,1,1]],"date-time":"2017-01-01T00:00:00Z","timestamp":1483228800000},"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":[[2017]]},"DOI":"10.1007\/978-3-319-59876-5_11","type":"book-chapter","created":{"date-parts":[[2017,6,1]],"date-time":"2017-06-01T01:09:35Z","timestamp":1496279375000},"page":"87-96","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Ejection Fraction Estimation Using a Wide Convolutional Neural Network"],"prefix":"10.1007","author":[{"given":"AbdulWahab","family":"Kabani","sequence":"first","affiliation":[]},{"given":"Mahmoud R.","family":"El-Sakka","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2017,6,2]]},"reference":[{"key":"11_CR1","doi-asserted-by":"crossref","unstructured":"Deng, J., Dong, W., Socher, R., Li, L.J., Li, K., Fei-Fei, L.: ImageNet: a large-scale hierarchical image database. In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2009, pp. 248\u2013255. IEEE (2009)","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"11_CR2","doi-asserted-by":"crossref","unstructured":"Erhan, D., Szegedy, C., Toshev, A., Anguelov, D.: Scalable object detection using deep neural networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 2147\u20132154 (2014)","DOI":"10.1109\/CVPR.2014.276"},{"issue":"4","key":"11_CR3","doi-asserted-by":"publisher","first-page":"193","DOI":"10.1007\/BF00344251","volume":"36","author":"K Fukushima","year":"1980","unstructured":"Fukushima, K.: Neocognitron: a self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position. Biol. Cybern. 36(4), 193\u2013202 (1980)","journal-title":"Biol. Cybern."},{"issue":"11","key":"11_CR4","first-page":"2138","volume":"36","author":"G Germano","year":"1995","unstructured":"Germano, G., Kiat, H., Kavanagh, P.B., Moriel, M., Mazzanti, M., Su, H.T., Train, K.F.V., Berman, D.S.: Automatic quantification of ejection fraction from gated myocardial perfusion spect. J. Nucl. Med. 36(11), 2138 (1995)","journal-title":"J. Nucl. Med."},{"key":"11_CR5","unstructured":"Glorot, X., Bengio, Y.: Understanding the difficulty of training deep feedforward neural networks. In: International Conference on Artificial Intelligence and Statistics, pp. 249\u2013256 (2010)"},{"key":"11_CR6","unstructured":"Hinton, G.E., Srivastava, N., Krizhevsky, A., Sutskever, I., Salakhutdinov, R.R.: Improving neural networks by preventing co-adaptation of feature detectors. arXiv preprint arXiv:1207.0580 (2012)"},{"key":"11_CR7","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"678","DOI":"10.1007\/978-3-319-41501-7_76","volume-title":"Image Analysis and Recognition","author":"AW Kabani","year":"2016","unstructured":"Kabani, A.W., El-Sakka, M.R.: Estimating ejection fraction and left ventricle volume using deep convolutional networks. In: Campilho, A., Karray, F. (eds.) ICIAR 2016. LNCS, vol. 9730, pp. 678\u2013686. Springer, Cham (2016). doi:10.1007\/978-3-319-41501-7_76"},{"key":"11_CR8","unstructured":"Kaggle: Data science bowl cardiac challenge data. https:\/\/www.kaggle.com\/c\/second-annual-data-science-bowl. Accessed 19 Mar 2016"},{"issue":"3","key":"11_CR9","doi-asserted-by":"publisher","first-page":"245","DOI":"10.1016\/j.media.2004.06.015","volume":"8","author":"MR Kaus","year":"2004","unstructured":"Kaus, M.R., von Berg, J., Weese, J., Niessen, W., Pekar, V.: Automated segmentation of the left ventricle in cardiac MRI. Med. Image Anal. 8(3), 245\u2013254 (2004)","journal-title":"Med. Image Anal."},{"key":"11_CR10","unstructured":"Korshunova, I.: Diagnosing heart diseases with deep neural networks. http:\/\/irakorshunova.github.io\/2016\/03\/15\/heart.html. Accessed 01 Feb 2017"},{"key":"11_CR11","unstructured":"Krizhevsky, A., Sutskever, I., Hinton, G.E.: Imagenet classification with deep convolutional neural networks. In: Advances in neural information processing systems, pp. 1097\u20131105 (2012)"},{"issue":"11","key":"11_CR12","doi-asserted-by":"publisher","first-page":"2278","DOI":"10.1109\/5.726791","volume":"86","author":"Y LeCun","year":"1998","unstructured":"LeCun, Y., Bottou, L., Bengio, Y., Haffner, P.: Gradient-based learning applied to document recognition. Proc. IEEE 86(11), 2278\u20132324 (1998)","journal-title":"Proc. IEEE"},{"key":"11_CR13","unstructured":"Lee, T., Liu, Q.: Solution to win the second annual data science bowl. https:\/\/github.com\/woshialex\/diagnose-heart. Accessed 01 Feb 2017"},{"key":"11_CR14","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"728","DOI":"10.1007\/11866565_89","volume-title":"Medical Image Computing and Computer-Assisted Intervention \u2013 MICCAI 2006","author":"X Lin","year":"2006","unstructured":"Lin, X., Cowan, B.R., Young, A.A.: Automated detection of left ventricle in 4D MR images: experience from a large study. In: Larsen, R., Nielsen, M., Sporring, J. (eds.) MICCAI 2006. LNCS, vol. 4190, pp. 728\u2013735. Springer, Heidelberg (2006). doi:10.1007\/11866565_89"},{"issue":"4","key":"11_CR15","doi-asserted-by":"publisher","first-page":"389","DOI":"10.1016\/j.compbiomed.2005.01.005","volume":"36","author":"M Lynch","year":"2006","unstructured":"Lynch, M., Ghita, O., Whelan, P.F.: Automatic segmentation of the left ventricle cavity and myocardium in MRI data. Comput. Biol. Med. 36(4), 389\u2013407 (2006)","journal-title":"Comput. Biol. Med."},{"key":"11_CR16","unstructured":"Mulholland, J.: Leading and winning team submissions analysis. http:\/\/www.datasciencebowl.com\/leading-and-winning-team-submissions-analysis\/. Accessed 04 Aug 2016"},{"key":"11_CR17","unstructured":"Nair, V., Hinton, G.E.: Rectified linear units improve restricted Boltzmann machines. In: Proceedings of the 27th International Conference on Machine Learning (ICML 2010), pp. 807\u2013814 (2010)"},{"issue":"285\u2013296","key":"11_CR18","first-page":"23","volume":"11","author":"N Otsu","year":"1975","unstructured":"Otsu, N.: A threshold selection method from gray-level histograms. Automatica 11(285\u2013296), 23\u201327 (1975)","journal-title":"Automatica"},{"key":"11_CR19","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"234","DOI":"10.1007\/978-3-319-24574-4_28","volume-title":"Medical Image Computing and Computer-Assisted Intervention \u2014 MICCAI 2015","author":"O Ronneberger","year":"2015","unstructured":"Ronneberger, O., Fischer, P., Brox, T.: U-net: convolutional networks for biomedical image segmentation. In: Navab, N., Hornegger, J., Wells, W.M., Frangi, A.F. (eds.) MICCAI 2015. LNCS, vol. 9351, pp. 234\u2013241. Springer, Cham (2015). doi:10.1007\/978-3-319-24574-4_28"},{"issue":"3","key":"11_CR20","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1007\/s11263-015-0816-y","volume":"115","author":"O Russakovsky","year":"2015","unstructured":"Russakovsky, O., Deng, J., Su, H., Krause, J., Satheesh, S., Ma, S., Huang, Z., Karpathy, A., Khosla, A., Bernstein, M., et al.: Imagenet large scale visual recognition challenge. Int. J. Comput. Vis. 115(3), 211\u2013252 (2015)","journal-title":"Int. J. Comput. Vis."},{"key":"11_CR21","unstructured":"Sermanet, P., Eigen, D., Zhang, X., Mathieu, M., Fergus, R., LeCun, Y.: OverFeat: integrated recognition, localization and detection using convolutional networks. arXiv preprint arXiv:1312.6229 (2013)"},{"key":"11_CR22","unstructured":"Simonyan, K., Zisserman, A.: Very deep convolutional networks for large-scale image recognition. arXiv preprint arXiv:1409.1556 (2014)"},{"key":"11_CR23","unstructured":"Song, H.O., Girshick, R., Jegelka, S., Mairal, J., Harchaoui, Z., Darrell, T.: On learning to localize objects with minimal supervision. arXiv preprint arXiv:1403.1024 (2014)"},{"issue":"1","key":"11_CR24","first-page":"1929","volume":"15","author":"N Srivastava","year":"2014","unstructured":"Srivastava, N., Hinton, G., Krizhevsky, A., Sutskever, I., Salakhutdinov, R.: Dropout: a simple way to prevent neural networks from overfitting. J. Mach. Learn. Res. 15(1), 1929\u20131958 (2014)","journal-title":"J. Mach. Learn. Res."},{"key":"11_CR25","doi-asserted-by":"crossref","unstructured":"Szegedy, C., Liu, W., Jia, Y., Sermanet, P., Reed, S., Anguelov, D., Erhan, D., Vanhoucke, V., Rabinovich, A.: Going deeper with convolutions. arXiv preprint arXiv:1409.4842 (2014)","DOI":"10.1109\/CVPR.2015.7298594"},{"key":"11_CR26","unstructured":"Szegedy, C., Toshev, A., Erhan, D.: Deep neural networks for object detection. In: Advances in Neural Information Processing Systems, pp. 2553\u20132561 (2013)"},{"key":"11_CR27","unstructured":"de Wit, J.: Third place solution for the second kaggle national datascience bowl. https:\/\/github.com\/juliandewit\/kaggle_ndsb2. Accessed 01 Feb 2017"}],"container-title":["Lecture Notes in Computer Science","Image Analysis and Recognition"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-59876-5_11","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,5,16]],"date-time":"2024-05-16T12:03:42Z","timestamp":1715861022000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-319-59876-5_11"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017]]},"ISBN":["9783319598758","9783319598765"],"references-count":27,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-59876-5_11","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2017]]},"assertion":[{"value":"2 June 2017","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICIAR","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Image Analysis and Recognition","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Montreal, QC","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Canada","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2017","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5 July 2017","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"7 July 2017","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"iciar2017","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.aimiconf.org\/iciar17\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}