{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,30]],"date-time":"2024-10-30T18:16:10Z","timestamp":1730312170055,"version":"3.28.0"},"reference-count":23,"publisher":"SPIE","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,4,7]]},"DOI":"10.1117\/12.2655267","type":"proceedings-article","created":{"date-parts":[[2023,4,6]],"date-time":"2023-04-06T15:54:08Z","timestamp":1680796448000},"page":"35","source":"Crossref","is-referenced-by-count":0,"title":["Correcting class imbalances with self-training for improved universal lesion detection and tagging"],"prefix":"10.1117","author":[{"given":"Alexander Te-Wei","family":"Shieh","sequence":"first","affiliation":[]},{"given":"Tejas Sudharshan","family":"Mathai","sequence":"additional","affiliation":[]},{"given":"Jianfei","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Angshuman","family":"Paul","sequence":"additional","affiliation":[]},{"given":"Ronald M.","family":"Summers","sequence":"additional","affiliation":[]}],"member":"189","reference":[{"key":"c1","doi-asserted-by":"publisher","DOI":"10.2214\/AJR.09.4110"},{"key":"c2","doi-asserted-by":"publisher","DOI":"10.1117\/1.JMI.5.3.036501"},{"key":"c3","first-page":"878","article-title":"Universal lesion detection in CT scans using neural network ensembles","volume-title":"Medical Imaging 2022: Computer-Aided Diagnosis","volume":"12033","author":"Mattikalli","year":"2022"},{"key":"c4","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-59719-1"},{"key":"c5","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.42"},{"key":"c6","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2020.3047598"},{"key":"c7","first-page":"321","article-title":"ULDOR: a universal lesion detector for ct scans with pseudo masks and hard negative example mining","author":"Tang","year":"2019","journal-title":"ISBI"},{"key":"c8","first-page":"921","article-title":"Recist-net: Lesion detection via grouping keypoints on recist-based annotation","author":"Xie","year":"2021","journal-title":"ISBI"},{"key":"c9","article-title":"Improving retinanet for ct lesion detection with dense masks from weak recist labels","author":"Zlocha","year":"2019","journal-title":"MICCAI"},{"key":"c10","first-page":"511","article-title":"3d context enhanced region-based convolutional neural network for end-to-end lesion detection","author":"Yan","year":"2018","journal-title":"MICCAI 2018"},{"key":"c11","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-87240-3"},{"key":"c12","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-16437-8"},{"key":"c13","doi-asserted-by":"crossref","first-page":"8515","DOI":"10.1109\/CVPR.2019.00872","article-title":"Holistic and comprehensive annotation of clinically significant findings on diverse ct images: Learning from radiology reports and label ontology","volume-title":"2019 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","author":"Yan","year":"2019"},{"key":"c14","first-page":"194","article-title":"MULAN: Multitask universal lesion analysis network for joint lesion detection, tagging, and segmentation","author":"Yan","year":"2019","journal-title":"MICCAI"},{"key":"c15","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-16760-7"},{"key":"c16","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-16760-7"},{"key":"c17","article-title":"Varifocalnet: An iou-aware dense object detector","author":"Zhang","year":"2021","journal-title":"CVPR"},{"key":"c18","article-title":"Varifocalnet: An iou-aware dense object detector","author":"Zhang","year":"2021","journal-title":"CVPR"},{"key":"c19","doi-asserted-by":"publisher","DOI":"10.1016\/j.imavis.2021.104117"},{"article-title":"Yolox: Exceeding yolo series in 2021","year":"2019","author":"Ge","key":"c20"},{"key":"c21","article-title":"Deformable detr: Deformable transformers for end-to-end object detection","volume-title":"International Conference on Learning Representations","author":"Zhu","year":"2021"},{"key":"c22","doi-asserted-by":"crossref","first-page":"589","DOI":"10.1007\/978-3-030-58526-6_35","article-title":"Improving object detection with selective self-supervised self-training","volume-title":"Computer Vision \u2013 ECCV 2020: 16th European Conference","author":"Li","year":"2020"},{"key":"c23","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2022.02.012"}],"event":{"name":"Computer-Aided Diagnosis","start":{"date-parts":[[2023,2,19]]},"location":"San Diego, United States","end":{"date-parts":[[2023,2,24]]}},"container-title":["Medical Imaging 2023: Computer-Aided Diagnosis"],"original-title":[],"deposited":{"date-parts":[[2023,4,24]],"date-time":"2023-04-24T19:04:48Z","timestamp":1682363088000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.spiedigitallibrary.org\/conference-proceedings-of-spie\/12465\/2655267\/Correcting-class-imbalances-with-self-training-for-improved-universal-lesion\/10.1117\/12.2655267.full"}},"subtitle":[],"editor":[{"given":"Khan M.","family":"Iftekharuddin","sequence":"additional","affiliation":[]},{"given":"Weijie","family":"Chen","sequence":"additional","affiliation":[]}],"short-title":[],"issued":{"date-parts":[[2023,4,7]]},"references-count":23,"URL":"https:\/\/doi.org\/10.1117\/12.2655267","relation":{},"subject":[],"published":{"date-parts":[[2023,4,7]]}}}