Cardiac Imaging: Page 60

3D software fuses CCTA and CT perfusion images
By Abraham Kim
Monday, November 27 | 3:30 p.m.-3:40 p.m. | SSE04-04 | Room S504AB3D fusion imaging software allows for one-stop-shop diagnostic assessment of coronary artery disease by combining coronary CT angiography (CCTA) and CT myocardial perfusion images, according to Swiss researchers.
November 7, 2017
Digirad revenues dip, net loss widens in Q3
By AuntMinnie.com staff writers
Slower than expected sales of capital equipment led to an 8% drop in revenue and a significantly higher net loss for nuclear medicine firm Digirad in its third quarter.
November 6, 2017
HeartFlow highlights new APC code for FFR-CT software
By AuntMinnie.com staff writers
Cardiovascular software developer HeartFlow said the U.S. Centers for Medicare and Medicaid Services has finalized a new technology ambulatory payment classification (APC) code for its software that analyzes CT images to calculate fractional flow reserve (FFR-CT).
November 5, 2017
Deep learning can predict stenosis on fast SPECT-MPI
By Erik L. Ridley
Friday, December 1 | 11:00 a.m.-11:10 a.m. | SST02-04 | Room E450AResearchers have found that deep learning can improve the detection of potentially significant ischemic defects on raw, high-speed SPECT myocardial perfusion imaging (MPI) studies.
November 5, 2017
Deep learning can quantify fat around the heart
By Erik L. Ridley
Friday, December 1 | 10:30 a.m.-10:40 a.m. | SST02-01 | Room E450AA deep-learning algorithm can rapidly segment and quantify the volume of thoracic fat surrounding the heart, according to researchers from Cedars-Sinai.
November 5, 2017
Deep learning may sharply increase specificity of CCTA
By Erik L. Ridley
Thursday, November 30 | 11:50 a.m.-12:00 p.m. | SSQ02-09 | Room S502ABThe combination of a deep-learning algorithm and visual stenosis grading could significantly boost the specificity of coronary CT angiography (CCTA) for detecting functionally significant stenosis, a Dutch team has found.
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
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
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
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
What factors delay lung cancer diagnosis on CT CAC?
By Abraham Kim
Wednesday, November 29 | 3:50 p.m.-4:00 p.m. | SSM04-06 | Room S504ABCT for coronary artery calcium (CAC) scoring is susceptible to detection and interpretation errors that may delay the diagnosis of lung cancer, according to researchers from South Korea.
November 1, 2017
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