{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,12]],"date-time":"2026-07-12T10:05:23Z","timestamp":1783850723276,"version":"3.55.0"},"reference-count":22,"publisher":"IEEE","license":[{"start":{"date-parts":[[2021,4,13]],"date-time":"2021-04-13T00:00:00Z","timestamp":1618272000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,4,13]],"date-time":"2021-04-13T00:00:00Z","timestamp":1618272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,4,13]],"date-time":"2021-04-13T00:00:00Z","timestamp":1618272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,4,13]]},"DOI":"10.1109\/isbi48211.2021.9433761","type":"proceedings-article","created":{"date-parts":[[2021,5,25]],"date-time":"2021-05-25T20:14:15Z","timestamp":1621973655000},"page":"1677-1681","source":"Crossref","is-referenced-by-count":30,"title":["Defending Against Adversarial Attacks On Medical Imaging Ai System, Classification Or Detection?"],"prefix":"10.1109","author":[{"given":"Xin","family":"Li","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Deng","family":"Pan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dongxiao","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref10","article-title":"Are labels required for improving adversarial robustness?","author":"stanforth","year":"2019","journal-title":"arXiv preprint arXiv 1905 10520"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00498"},{"key":"ref12","article-title":"Improving adversarial robustness via probabilistically compact loss with logit constraints","author":"li","year":"2020","journal-title":"2012 arXiv preprint arXiv"},{"key":"ref13","article-title":"Understanding adversarial attacks on deep learning based medical image analysis systems","author":"ma","year":"2019","journal-title":"arXiv preprint arXiv 1907 11634"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i04.5907"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/ISBI45749.2020.9098628"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33018417"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.01160"},{"key":"ref18","article-title":"Characterizing adversarial sub-spaces using local intrinsic dimensionality","author":"ma","year":"2018","journal-title":"arXiv preprint arXiv 1801 02929"},{"key":"ref19","article-title":"Detecting adversarial samples from artifacts","author":"feinman","year":"2017","journal-title":"arXiv preprint arXiv 1703 00410"},{"key":"ref4","article-title":"Generalizability vs. robustness: adversarial examples for medical imaging","author":"paschali","year":"2018","journal-title":"arXiv preprint arXiv 1804 00209"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/BIBM49941.2020.9313217"},{"key":"ref6","article-title":"Explaining and harnessing adversarial examples","author":"goodfellow","year":"2014","journal-title":"arXiv preprint arXiv 1412 6572"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-32245-8_34"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2017.49"},{"key":"ref7","article-title":"Towards deep learning models resistant to adversarial attacks","author":"madry","year":"2017","journal-title":"arXiv preprint arXiv 1706 06083"},{"key":"ref2","article-title":"Vispi: Automatic visual perception and interpretation of chest x-rays","author":"li","year":"2019","journal-title":"arXiv preprint arXiv 1906 05190"},{"key":"ref1","article-title":"Chexnet: Radiologist-level pneumonia detection on chest x-rays with deep learning","author":"rajpurkar","year":"2017","journal-title":"arXiv preprint arXiv 1711 05225"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1016\/j.cell.2018.02.010"},{"key":"ref20","first-page":"2825","article-title":"Scikit-learn: Machine learning in Python","volume":"12","author":"pedregosa","year":"2011","journal-title":"Journal of Machine Learning Research"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0118432"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"}],"event":{"name":"2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI)","location":"Nice, France","start":{"date-parts":[[2021,4,13]]},"end":{"date-parts":[[2021,4,16]]}},"container-title":["2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9433749\/9433753\/09433761.pdf?arnumber=9433761","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,10]],"date-time":"2022-05-10T15:41:52Z","timestamp":1652197312000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9433761\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,4,13]]},"references-count":22,"URL":"https:\/\/doi.org\/10.1109\/isbi48211.2021.9433761","relation":{},"subject":[],"published":{"date-parts":[[2021,4,13]]}}}