{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,24]],"date-time":"2025-11-24T21:33:58Z","timestamp":1764020038237,"version":"3.28.0"},"reference-count":12,"publisher":"SPIE","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016,3,24]]},"DOI":"10.1117\/12.2217146","type":"proceedings-article","created":{"date-parts":[[2016,3,24]],"date-time":"2016-03-24T15:33:08Z","timestamp":1458833588000},"page":"97850P","source":"Crossref","is-referenced-by-count":25,"title":["Deep convolutional networks for automated detection of posterior-element fractures on spine CT"],"prefix":"10.1117","volume":"9785","author":[{"given":"Holger R.","family":"Roth","sequence":"additional","affiliation":[]},{"given":"Yinong","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Jianhua","family":"Yao","sequence":"additional","affiliation":[]},{"given":"Le","family":"Lu","sequence":"additional","affiliation":[]},{"given":"Joseph E.","family":"Burns","sequence":"additional","affiliation":[]},{"given":"Ronald M.","family":"Summers","sequence":"additional","affiliation":[]}],"member":"189","reference":[{"key":"c1","doi-asserted-by":"publisher","DOI":"10.1007\/s00586-009-1123-5"},{"key":"c2","doi-asserted-by":"publisher","DOI":"10.1016\/j.compmedimag.2014.04.001"},{"key":"c3","first-page":"1097","article-title":"Imagenet classification with deep convolutional neural networks","author":"Krizhevsky","year":"2012"},{"key":"c4","first-page":"818","article-title":"Visualizing and understanding convolutional networks","author":"Zeiler","year":"2014"},{"key":"c5","first-page":"449","article-title":"Bodypart recognition using multi-stage deep learning","author":"Yan","year":"2015"},{"key":"c6","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-40763-5"},{"key":"c7","first-page":"520","article-title":"A new 2.5 d representation for lymph node detection using random sets of deep convolutional neural network observations","author":"Roth","year":"2014"},{"article-title":"Improving computer-aided detection using convolutional neural networks and random view aggregation","year":"2015","author":"Roth","key":"c8"},{"issue":"1","key":"c9","first-page":"1929","article-title":"Dropout: A simple way to prevent neural networks from overfitting","volume":"15","author":"Srivastava","year":"2014"},{"article-title":"Multi-atlas segmentation with joint label fusion of osteoporotic vertebral compression fractures on ct","year":"2015","author":"Wang","key":"c10"},{"key":"c11","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2012.143"},{"key":"c12","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-24571-3"}],"event":{"name":"SPIE Medical Imaging","location":"San Diego, California, United States"},"container-title":["SPIE Proceedings","Medical Imaging 2016: Computer-Aided Diagnosis"],"original-title":[],"deposited":{"date-parts":[[2018,9,27]],"date-time":"2018-09-27T19:55:29Z","timestamp":1538078129000},"score":1,"resource":{"primary":{"URL":"http:\/\/proceedings.spiedigitallibrary.org\/proceeding.aspx?doi=10.1117\/12.2217146"}},"subtitle":[],"editor":[{"given":"Georgia D.","family":"Tourassi","sequence":"first","affiliation":[]},{"given":"Samuel G.","family":"Armato","sequence":"additional","affiliation":[]}],"short-title":[],"issued":{"date-parts":[[2016,3,24]]},"references-count":12,"URL":"https:\/\/doi.org\/10.1117\/12.2217146","relation":{},"ISSN":["0277-786X"],"issn-type":[{"type":"print","value":"0277-786X"}],"subject":[],"published":{"date-parts":[[2016,3,24]]}}}