{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,24]],"date-time":"2025-10-24T08:18:09Z","timestamp":1761293889833,"version":"3.28.0"},"reference-count":37,"publisher":"IEEE","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018,12]]},"DOI":"10.1109\/bibm.2018.8621432","type":"proceedings-article","created":{"date-parts":[[2019,2,28]],"date-time":"2019-02-28T22:32:01Z","timestamp":1551393121000},"page":"899-906","source":"Crossref","is-referenced-by-count":10,"title":["A Novel Radiogenomics Framework for Genomic and Image Feature Correlation using Deep Learning"],"prefix":"10.1109","author":[{"given":"Shuai","family":"Li","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hongze","family":"Han","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dong","family":"Sui","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Aimin","family":"Hao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hong","family":"Qin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref33","article-title":"Data From NSCLC-Radiomics-Genomics","author":"aerts","year":"2015","journal-title":"The Cancer Imaging Archive"},{"key":"ref32","article-title":"Data for NSCLC Radiogenomics Collection","author":"bakr","year":"2017","journal-title":"The Cancer Imaging Archive"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.12111607"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2017.10.029"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-00937-3_71"},{"key":"ref36","doi-asserted-by":"crossref","DOI":"10.1007\/978-3-030-00934-2_81","article-title":"CT-Realistic Lung Nodule Simulation from 3D Conditional Generative Adversarial Networks for Robust Lung Segmentation[J]","author":"jin","year":"2018"},{"key":"ref35","article-title":"Adam: A method for stochastic optimization[J]","author":"kingma","year":"2014","journal-title":"arXiv preprint arXiv 1412 6980"},{"key":"ref34","first-page":"694","article-title":"Perceptual losses for real-time style transfer and super-resolution[C]","author":"johnson","year":"2016","journal-title":"European conference on computer vision Springer Cham"},{"key":"ref10","first-page":"506","article-title":"Automatic Brain Tumor Detection and Segmentation Using U-Net Based Fully Convolutional Networks[J]","author":"dong","year":"2017"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2018.2823768"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2017.2713099"},{"key":"ref13","article-title":"Deep Residual Learning for Compressed Sensing CT Reconstruction via Persistent Homology Analysis[J]","author":"han","year":"2016","journal-title":"arXiv preprint arXiv 1611 06391"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00968"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2017.02.035"},{"key":"ref16","first-page":"2672","article-title":"Generative Adversarial Networks[J]","volume":"3","author":"goodfellow","year":"2014","journal-title":"Advances in neural information processing systems"},{"key":"ref17","article-title":"Unsupervised representation learning with deep convolutional generative adversarial networks[J]","author":"radford","year":"2015","journal-title":"arXiv preprint arXiv 1511 05271"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2015.2458702"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/ICDMW.2016.0041"},{"key":"ref28","article-title":"Pattern Classification for Gastrointestinal Stromal Tumors by Integration of Radiomics and Deep Convolutional Features[J]","author":"ning","year":"2018","journal-title":"IEEE Journal of Biomedical and Health Informatics"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2016.2528129"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.21037\/tlcr.2017.09.07"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1146\/annurev-bioeng-071812-152416"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.radonc.2015.02.015"},{"key":"ref29","article-title":"Deep learning Radiomics of shear wave elastography significantly improved diagnostic performance for assessing liver fibrosis in chronic hepatitis B: a prospective multicentre study[J]","author":"wang","year":"2018","journal-title":"Gut"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2016.2535865"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/3DV.2016.79"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1038\/ncomms5006"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.lungcan.2017.10.015"},{"key":"ref9","first-page":"234","article-title":"U-Net: Convolutional Networks for Biomedical Image Segmentation[C]\/\/","author":"ronneberger","year":"2015","journal-title":"International Conference on Medical image computing and computer-assisted intervention Springer Cham"},{"key":"ref1","doi-asserted-by":"crossref","first-page":"524","DOI":"10.1001\/jamaoncol.2016.5688","article-title":"Global, regional, and national cancer incidence, mortality, years of life lost, years lived with disability, and disability-adjusted life-years for 32 cancer groups, 1990 to 2015: a systematic analysis for the global burden of disease study[J]","volume":"3","author":"fitzmaurice","year":"2017","journal-title":"JAMA Oncology"},{"key":"ref20","first-page":"2672","article-title":"Conditional Generative Adversarial Nets[J]","author":"mirza","year":"2014","journal-title":"Computer Science"},{"key":"ref22","first-page":"417","article-title":"Medical image synthesis with context-aware generative adversarial networks[C]","author":"nie","year":"2017","journal-title":"International Conference on Medical image computing and computer-assisted intervention Springer Cham"},{"key":"ref21","article-title":"SCAN: Structure Correcting Adversarial Network for Organ Segmentation in Chest X-rays[J]","author":"dai","year":"2017","journal-title":"arXiv preprint arXiv 1703 01281"},{"key":"ref24","first-page":"49","article-title":"Virtual PET Images from CT Data Using Deep Convolutional Networks: Initial Results[J]","author":"cohen","year":"2017"},{"key":"ref23","first-page":"146","article-title":"Unsupervised Anomaly Detection with Generative Adversarial Networks to Guide Marker Discovery[J]","author":"schlegl","year":"2017"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1631\/jzus.B1700260"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejmp.2017.10.008"}],"event":{"name":"2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","start":{"date-parts":[[2018,12,3]]},"location":"Madrid, Spain","end":{"date-parts":[[2018,12,6]]}},"container-title":["2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/8609864\/8621069\/08621432.pdf?arnumber=8621432","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,8,23]],"date-time":"2020-08-23T23:06:34Z","timestamp":1598223994000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8621432\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,12]]},"references-count":37,"URL":"https:\/\/doi.org\/10.1109\/bibm.2018.8621432","relation":{},"subject":[],"published":{"date-parts":[[2018,12]]}}}