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Imaging Informatics: Page 354
Deep-learning reconstruction improves coronary MR angiography
By
Wayne Forrest
Wednesday, November 28 | 11:40 a.m.-11:50 a.m. | SSK03-08 | Room S102CDIn this session, Japanese researchers will share results from their newly developed deep-learning reconstruction technique designed to improve image quality for noncontrast coronary MR angiography.
October 30, 2018
Using deep learning, MRI may help combat common brain tumor
By
Wayne Forrest
Tuesday, November 27 | 11:50 a.m.-12:00 p.m. | SSG10-09 | Room E353ACombining a deep-learning algorithm with quantitative MRI could help advance treatment and survival for patients with glioblastoma multiforme.
October 30, 2018
Deep learning could aid MRI to detect mesial temporal sclerosis
By
Wayne Forrest
Monday, November 26 | 3:10 p.m.-3:20 p.m. | SSE19-02 | Room E352In this session, researchers will describe their early success in developing a deep-learning method featuring a convolutional neural network to help MRI detect mesial temporal sclerosis in epilepsy patients.
October 30, 2018
Deep learning with MRI mimics cardiac technologists
By
Wayne Forrest
Monday, November 26 | 3:00 p.m.-3:10 p.m. | SSE04-01 | Room N226Researchers are reporting success with a deep-learning convolutional neural network designed to localize key cardiac landmarks to help with complex examinations such as cardiac MRI.
October 30, 2018
Mach7, Client Outlook win Hong Kong deal
By
AuntMinnie.com staff writers
Data management firm Mach7 Technologies and image viewing software developer Client Outlook have received an enterprise imaging contract from the Hospital Authority of Hong Kong.
October 29, 2018
Candelis deploys ImageGrid Plus system at Duke
By
AuntMinnie.com staff writers
Image software and archiving firm Candelis has installed its new ImageGrid Plus system at Duke University Hospitals in North Carolina.
October 29, 2018
Machine learning can predict stroke treatment outcomes
By
Erik L. Ridley
Making use of imaging features and demographic information, machine-learning algorithms predicted 90-day outcomes in patients with acute ischemic stroke, offering potential as an aid for treatment decisions, according to research published online October 24 in the
American Journal of Roentgenology
.
October 29, 2018
AI-based CAD can improve breast cancer detection
By
Erik L. Ridley
Wednesday, November 28 | 11:30 a.m.-11:40 a.m. | SSK02-07 | Room E451BComputer-aided detection (CAD) software based on artificial intelligence (AI) can increase radiologist breast cancer detection rates, according to this scientific presentation.
October 29, 2018
In-house data train breast cancer detection algorithm
By
Erik L. Ridley
Wednesday, November 28 | 11:20 a.m.-11:30 a.m. | SSK02-06 | Room E451BResearchers from California will share how deep-learning algorithms for breast cancer detection can be trained using an in-house image database.
October 29, 2018
Deep-learning networks help classify breast density
By
Kate Madden Yee
Wednesday, November 28 | 10:40 a.m.-10:50 a.m. | SSK02-02 | Room E451BDeep-learning networks can help classify breast tissue density, according to researchers from NYU Langone Medical Center.
October 29, 2018
Deep learning may yield sharply lower dose from DBT
By
Erik L. Ridley
Monday, November 26 | 3:00 p.m.-3:10 p.m. | SSE23-01 | Room S502ABIn this scientific session, a multi-institutional team of researchers will share how deep-learning technology could lead to nearly 80% lower radiation dose to patients from digital breast tomosynthesis (DBT) studies.
October 29, 2018
AI speeds up DBT reading time, helps find more cancers
By
Erik L. Ridley
Monday, November 26 | 11:20 a.m.-11:30 a.m. | RC215-14 | Arie Crown TheaterIn this talk, researchers will report that the concurrent use of artificial intelligence (AI) software while interpreting digital breast tomosynthesis (DBT) screening exams leads to higher radiologist accuracy and much faster reading times.
October 29, 2018
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