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CT: Page 206

Algorithm virtually enhances resolution of microdose CT
By Abraham Kim
Tuesday, November 28 | 3:10 p.m.-3:20 p.m. | SSJ22-02 | Room S403BA major drawback of lowering CT radiation dose is a loss in image quality, but researchers found that microdose CT can deliver high-quality scans with the aid of a deep-learning algorithm.
November 5, 2017
Deep learning can spot significant coronary stenosis
By Erik L. Ridley
Tuesday, November 28 | 11:50 a.m.-12:00 p.m. | SSG02-09 | Room S504ABIn this session, researchers will describe how deep learning shows potential for identifying patients with functionally significant coronary artery stenosis.
November 5, 2017
AI assesses cardiovascular risk on routine chest CT
By Erik L. Ridley
Tuesday, November 28 | 11:40 a.m.-11:50 a.m. | SSG13-08 | Room S404ABA Dutch team has found that its artificial intelligence (AI) algorithm can automatically perform cardiovascular risk assessment from routine chest CT studies.
November 5, 2017
CAD enables lower radiation dose in CT lung screening
By Abraham Kim
Tuesday, November 28 | 11:20 a.m.-11:30 a.m. | SSG13-06 | Room S404ABIn this talk, researchers will describe how computer-aided detection (CAD) can lead to marked reductions in radiation dose on low-dose CT lung cancer screening scans, even when image slice thickness is altered.
November 5, 2017
Deep learning yields real-time coronary calcium scoring
By Erik L. Ridley
Tuesday, November 28 | 10:50 a.m.-11:00 a.m. | SSG13-03 | Room S404ABA deep-learning algorithm can swiftly quantify coronary artery calcium scores on low-dose CT lung screening exams, according to researchers from the Netherlands.
November 5, 2017
Algorithm detects, segments lung nodules on CT
By Erik L. Ridley
Tuesday, November 28 | 10:40 a.m.-10:50 a.m. | SSG13-02 | Room S404ABIn this scientific session, a team from imaging software developer Arterys will present its deep learning-based approach to detecting and segmenting lung nodules on CT scans.
November 5, 2017
Machine learning helps predict lithotripsy outcome
By Erik L. Ridley
Monday, November 27 | 3:50 p.m.-4:00 p.m. | SSE12-06 | Room E353AA Swiss group will present its experience in using CT texture analysis and machine learning to predict the successful treatment of kidney stones with shock-wave lithotripsy.
November 5, 2017
AI can detect, characterize kidney stones
By Erik L. Ridley
Monday, November 27 | 3:40 p.m.-3:50 p.m. | SSE12-05 | Room E353AAn artificial intelligence (AI) algorithm can be used to accurately detect and characterize kidney stones, according to researchers from Boston.
November 5, 2017
Machine learning may enhance utility of FFR-CT
By Erik L. Ridley
Sunday, November 26 | 11:45 a.m.-11:55 a.m. | SSA04-07 | Room S504ABA machine-learning algorithm shows potential for facilitating the use of fractional flow reserve (FFR) calculations on coronary CT angiography studies, according to research being presented in this scientific session.
November 5, 2017
ACR chair asks Congress for radiation research funds
By AuntMinnie.com staff writers
The American College of Radiology (ACR) is urging a U.S. House of Representatives subcommittee to provide funding for low-dose medical radiation research to ensure future safety practices.
November 1, 2017
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More lung cancer facilities may not mean more screening
By Abraham Kim
Thursday, November 30 | 11:50 a.m.-12:00 p.m. | SSQ05-09 | Room S402ABThe availability of screening facilities does not necessarily affect lung cancer outcomes, according to this preliminary analysis of the American College of Radiology Lung Cancer Screening Registry.
November 1, 2017
Who uses CCTA more: radiologists or cardiologists?
By Abraham Kim
Thursday, November 30 | 11:40 a.m.-11:50 a.m. | SSQ02-08 | Room S502ABThe ongoing tug-of-war between radiologists and cardiologists may be starting to favor one end: Radiologists now utilize coronary CT angiography (CCTA) at a higher rate than cardiologists do, according to this presentation.
November 1, 2017
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