{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,30]],"date-time":"2025-12-30T17:47:13Z","timestamp":1767116833530,"version":"3.28.0"},"reference-count":13,"publisher":"SPIE","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016,3,24]]},"DOI":"10.1117\/12.2214876","type":"proceedings-article","created":{"date-parts":[[2016,3,24]],"date-time":"2016-03-24T15:33:08Z","timestamp":1458833588000},"page":"978532","source":"Crossref","is-referenced-by-count":54,"title":["Lung nodule detection using 3D convolutional neural networks trained on weakly labeled data"],"prefix":"10.1117","volume":"9785","author":[{"given":"Rushil","family":"Anirudh","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jayaraman J.","family":"Thiagarajan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Timo","family":"Bremer","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hyojin","family":"Kim","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"189","reference":[{"key":"c1","doi-asserted-by":"publisher","DOI":"10.1038\/nature14539"},{"key":"c2","unstructured":"http:\/\/www.lung.org\/lung-disease\/lung-cancer\/lung-cancer-screening-guidelines\/lung-cancer-screening-for-patients.pdf. [accessed 13-Aug-2015]."},{"key":"c3","doi-asserted-by":"publisher","DOI":"10.4103\/0256-4602.101306"},{"key":"c4","first-page":"133","article-title":"Lung nodule classification using deep features in ct images,","author":"Kumar","year":"2015"},{"key":"c5","first-page":"286","article-title":"Off-the-shelf convolutional neural network features for pulmonary nodule detection in computed tomography scans,","author":"van Ginneken","year":"2015"},{"key":"c6","doi-asserted-by":"publisher","DOI":"10.1016\/j.cmpb.2013.08.015"},{"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"},{"key":"c8","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2012.120"},{"key":"c9","first-page":"1097","article-title":"Imagenet classification with deep convolutional neural networks,","author":"Krizhevsky","year":"2012"},{"key":"c10","unstructured":"\u201cSpie-aapm-nci lung nodule classification challenge dataset.\u201d https:\/\/wiki.cancerimagingarchive.net\/display\/DOI\/SPIE-AAPM-NCI+Lung+Nodule+Classification+Challenge+Dataset. [accessed 13-Aug-2015]."},{"key":"c11","doi-asserted-by":"publisher","DOI":"10.1117\/1.JMI.2.2.020103"},{"article-title":"Matconvnet-convolutional neural networks for matlab,","year":"2014","author":"Vedaldi","key":"c12"},{"issue":"1","key":"c13","first-page":"1929","article-title":"Dropout: A simple way to prevent neural networks from overfitting,","volume":"15","author":"Srivastava","year":"2014"}],"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":"2018-09-27T20:33:04Z","timestamp":1538080384000},"score":1,"resource":{"primary":{"URL":"http:\/\/proceedings.spiedigitallibrary.org\/proceeding.aspx?doi=10.1117\/12.2214876"}},"subtitle":[],"editor":[{"given":"Georgia D.","family":"Tourassi","sequence":"first","affiliation":[],"role":[{"role":"editor","vocabulary":"crossref"}]},{"given":"Samuel G.","family":"Armato","sequence":"additional","affiliation":[],"role":[{"role":"editor","vocabulary":"crossref"}]}],"short-title":[],"issued":{"date-parts":[[2016,3,24]]},"references-count":13,"URL":"https:\/\/doi.org\/10.1117\/12.2214876","relation":{},"ISSN":["0277-786X"],"issn-type":[{"type":"print","value":"0277-786X"}],"subject":[],"published":{"date-parts":[[2016,3,24]]}}}