Enterprise Imaging: Page 145

Deep learning shows promise for spotting prostate cancer
By Erik L. Ridley
Tuesday, November 29 | 12:15 p.m.-12:45 p.m. | IN229-SD-TUA6 | Lakeside, IN Community, Station 6In this poster presentation, researchers will highlight the potential of deep learning in detecting clinically significant prostate cancer on multiparametric MRI scans.
October 30, 2016
Deep learning detects, labels vertebrae on lumbar MRI
By Erik L. Ridley
Tuesday, November 29 | 12:15 p.m.-12:45 p.m. | IN227-SD-TUA4 | Lakeside, IN Community, Station 4A new study has shown that deep-learning technology can detect and label vertebrae on lumbar MRI studies.
October 30, 2016
Natural language processing, machine learning extract acute findings on reports
By Erik L. Ridley
Tuesday, November 29 | 10:50 a.m.-11:00 a.m. | SSG07-03 | Room S402ABIn this presentation, researchers will share how natural language processing and machine-learning technology can extract acute findings from radiology reports.
October 30, 2016
Deep learning may be able to avoid some breast biopsies
By Erik L. Ridley
Monday, November 28 | 3:20 p.m.-3:30 p.m. | SSE02-03 | Room E450ADeep-learning technology has the potential to help decrease the number of unnecessary biopsies performed on benign breast microcalcifications, according to this scientific presentation.
October 30, 2016
Deep learning can detect osteoporosis on CT exams
By Erik L. Ridley
Monday, November 28 | 12:15 p.m.-12:45 p.m. | IN212-SD-MOA3 | Lakeside, IN Community, Station 3Artificial intelligence based on deep-learning techniques may be able to automatically screen for osteoporosis in routine abdominal CT exams, according to this poster presentation.
October 30, 2016
Deep learning shows promise for reading chest x-rays
By Erik L. Ridley
Monday, November 28 | 12:15 p.m.-12:45 p.m. | IN211-SD-MOA2 | Lakeside, IN Community, Station 2A deep-learning method could be used to provide a more "human-like" diagnosis on chest x-rays, according to a group from the U.S. National Institutes of Health Clinical Center.
October 30, 2016
AI offers value as teaching tool for radiologists
By Erik L. Ridley
Monday, November 28 | 11:40 a.m.-11:50 a.m. | SSC08-08 | Room S402ABResearchers in this session will share how artificial intelligence (AI) technology can be used to teach people how to think like a radiologist and overcome common biases during image interpretation.
October 30, 2016
Deep learning + CADx combo performs best in breast tumors
By Erik L. Ridley
Monday, November 28 | 11:30 a.m.-11:40 a.m. | SSC08-07 | Room S402ABIn this talk, researchers will describe how the combination of deep convolutional neural networks and computer-assisted diagnosis (CADx) software yields improved diagnostic performance in differentiating breast tumors on full-field digital mammography and ultrasound.
October 30, 2016
Deep learning may help assess breast cancer risk
By Erik L. Ridley
Monday, November 28 | 9:00 a.m.-9:10 a.m. | RC215-03 | Arie Crown TheaterDeep learning may be able to help clinicians evaluate mammographic parenchymal patterns for assessing breast cancer risk, according to researchers from the University of Chicago.
October 30, 2016
Deep learning can find, label images in PACS
By Erik L. Ridley
Sunday, November 27 | 12:30 p.m.-1:00 p.m. | IN200-SD-SUA1 | Lakeside, IN Community, Station 1In this poster presentation, researchers will highlight the potential of deep-learning techniques for categorizing and labeling images stored on PACS archives.
October 30, 2016
It helps to correlate radiology, pathology in PACS
By Erik L. Ridley
Sunday, November 27 | 12:05 p.m.-12:15 p.m. | SSA12-09 | Room S403AIn this scientific presentation, researchers will describe how correlating radiology and pathology results within their PACS software yields time savings and efficiency gains for radiologists who perform image-guided procedures.
October 30, 2016
Inadequate history may not affect emergency radiology reads
By Erik L. Ridley
Sunday, November 27 | 11:35 a.m.-11:45 a.m. | SSA06-06 | Room N226In this presentation, researchers from a teleradiology services provider will share how a lack of adequate clinical history -- surprisingly -- did not lead to more interpretation errors on emergency radiology cases.
October 30, 2016
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