{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,7]],"date-time":"2026-04-07T16:01:33Z","timestamp":1775577693610,"version":"3.50.1"},"reference-count":18,"publisher":"IEEE","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017,4]]},"DOI":"10.1109\/isbi.2017.7950581","type":"proceedings-article","created":{"date-parts":[[2017,6,20]],"date-time":"2017-06-20T17:35:30Z","timestamp":1497980130000},"page":"552-556","source":"Crossref","is-referenced-by-count":28,"title":["Domain specific convolutional neural nets for detection of architectural distortion in mammograms"],"prefix":"10.1109","author":[{"given":"Rami","family":"Ben-Ari","sequence":"first","affiliation":[]},{"given":"Ayelet","family":"Akselrod-Ballin","sequence":"additional","affiliation":[]},{"given":"Leonid","family":"Karlinsky","sequence":"additional","affiliation":[]},{"given":"Sharbell","family":"Hashoul","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref10","first-page":"238","article-title":"Unregistered multiview mammogram analysis with pre-trained deep learning models","volume":"9350","author":"hefny","year":"2015","journal-title":"MICCAI"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.81"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/ISBI.2016.7493368"},{"key":"ref13","article-title":"Return of the devil in the details: Delving deep into convolutional nets","author":"chatfield","year":"2014","journal-title":"British Machine Vision Con-ference"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1023\/B:VISI.0000013087.49260.fb"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/34.1000236"},{"key":"ref16","article-title":"Faster R-CNN: Towards real-time object detection with region proposal networks","author":"shaoqing","year":"2015","journal-title":"NIPS"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1117\/12.770325"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46976-8_21"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/EMBC.2015.7318939"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-07887-8_84"},{"key":"ref6","first-page":"104","article-title":"Characterization of Architectural Distortion in Mammograms Based on Texture Analysis Using Support Vector Machine Classifier with Clinical Evaluation","author":"amit","year":"2016","journal-title":"J Digit Imaging"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1007\/s11548-012-0793-3"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2014.131"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.222"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TBME.2011.2128870"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1053\/crad.2001.0662"},{"key":"ref9","article-title":"Chest pathology detection using deep learning with non-medical training","author":"yaniv","year":"2015","journal-title":"ISBI"}],"event":{"name":"2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017)","location":"Melbourne, Australia","start":{"date-parts":[[2017,4,18]]},"end":{"date-parts":[[2017,4,21]]}},"container-title":["2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/7944115\/7950442\/07950581.pdf?arnumber=7950581","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2017,10,2]],"date-time":"2017-10-02T22:56:23Z","timestamp":1506984983000},"score":1,"resource":{"primary":{"URL":"http:\/\/ieeexplore.ieee.org\/document\/7950581\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,4]]},"references-count":18,"URL":"https:\/\/doi.org\/10.1109\/isbi.2017.7950581","relation":{},"subject":[],"published":{"date-parts":[[2017,4]]}}}