{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,21]],"date-time":"2026-01-21T07:54:00Z","timestamp":1768982040559,"version":"3.49.0"},"reference-count":30,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/OAPA.html"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2019]]},"DOI":"10.1109\/access.2019.2908724","type":"journal-article","created":{"date-parts":[[2019,4,1]],"date-time":"2019-04-01T18:39:42Z","timestamp":1554143982000},"page":"44709-44720","source":"Crossref","is-referenced-by-count":74,"title":["A Deep Learning Approach for Breast Invasive Ductal Carcinoma Detection and Lymphoma Multi-Classification in Histological Images"],"prefix":"10.1109","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9061-1187","authenticated-orcid":false,"given":"Nadia","family":"Brancati","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Giuseppe","family":"De Pietro","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Maria","family":"Frucci","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Daniel","family":"Riccio","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1186\/1687-6180-2014-17"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-40763-5_50"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2018.09.007"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.4103\/2153-3539.186902"},{"key":"ref14","author":"kingma","year":"2014","journal-title":"Adam A method for stochastic optimization"},{"key":"ref15","first-page":"1097","article-title":"ImageNet classification with deep convolutional neural networks","author":"krizhevsky","year":"2012","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/5.726791"},{"key":"ref17","author":"liu","year":"2017","journal-title":"Detecting cancer metastases on gigapixel pathology images"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1007\/s10916-017-0773-9"},{"key":"ref19","article-title":"Sparse autoencoder","volume":"72","author":"ng","year":"2011","journal-title":"Cs294a lecture notes"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2015.2458702"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2831280"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.2307\/3001968"},{"key":"ref3","author":"aresta","year":"2018","journal-title":"Grand challenge on breast cancer histology images bach"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2015.2476509"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1038\/ncomms12474"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/ICPR.2016.7900002"},{"key":"ref8","first-page":"1160","article-title":"Mitosis detection in breast cancer histology images via deep cascaded networks","author":"chen","year":"2016","journal-title":"Proc AAAI"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-93000-8_87"},{"key":"ref2","year":"2016","journal-title":"Lymphoma and IDC Datasets"},{"key":"ref9","article-title":"Automatic detection of invasive ductal carcinoma in whole slide images with convolutional neural networks","volume":"9041","author":"cruz-roa","year":"2014","journal-title":"Proc SPIE"},{"key":"ref1","year":"2014","journal-title":"ICPR MITOS-ATYPIA"},{"key":"ref20","author":"quan","year":"2016","journal-title":"Fusionnet A deep fully residual convolutional neural network for image segmentation in connectomics"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TBME.2015.2496264"},{"key":"ref21","first-page":"234","article-title":"U-NET: Convolutional networks for biomedical image segmentation","author":"ronneberger","year":"2015","journal-title":"Proc Int Conf Med Image Comput Comput -Assist Intervent"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2014.11.010"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.2016.7727519"},{"key":"ref26","author":"wang","year":"2016","journal-title":"Deep learning for identifying metastatic breast cancer"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2015.2493530"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/8600701\/08678759.pdf?arnumber=8678759","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,8,10]],"date-time":"2021-08-10T19:40:24Z","timestamp":1628624424000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8678759\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"references-count":30,"URL":"https:\/\/doi.org\/10.1109\/access.2019.2908724","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019]]}}}