Imaging Informatics: Page 355

Deep learning elevates mammography CAD performance
By Erik L. Ridley
Monday, November 26 | 11:10 a.m.-11:20 a.m. | RC215-13 | Arie Crown TheaterMammography computer-aided detection (CAD) software based on deep learning can perform comparably to radiologists in detecting breast cancer and at a higher level than traditional mammography CAD applications, according to Dutch researchers.
October 29, 2018
eRAD expands its client list
By AuntMinnie.com staff writers
RIS/PACS vendor eRAD announced that Lauderdale Radiology Group has successfully deployed eRAD PACS as part of an expansion in its service offering.
October 28, 2018
Apple gets patent for new 3D printing technique
By AuntMinnie.com staff writers
Technology company Apple has received approval for a U.S. patent, No. 10,105,905, covering the 3D printing of models using a method that approximates the original shape of objects as a collection of small triangles.
October 28, 2018
5 reasons why imaging AI is different from CAD
By Elad Walach
Artificial intelligence (AI) in medical imaging is on the rise and already becoming part of the standard of care. But with all the hype, one must ask: Is next-generation imaging AI simply a new take on computer-aided detection/diagnosis (CAD)? Aidoc CEO Elad Walach presents five reasons why AI is fundamentally different.
October 28, 2018
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Road to RSNA 2018: Artificial Intelligence Preview
By Erik L. Ridley
Welcome to the first installment of this year's Road to RSNA preview of the RSNA 2018 meeting in Chicago. For the 10th year in a row, we're providing a modality-by-modality overview of selected scientific presentations to serve as your guide to events at McCormick Place. Our journey along the Road to RSNA begins with our preview of artificial intelligence (AI). Researchers will travel to the Windy City to share their experiences working with and developing AI applications in all aspects of the imaging process.
October 28, 2018
2017 11 02 17 42 1107 Road To Rsna 400
AI algorithm can triage routine abdominal CT exams
By Erik L. Ridley
Thursday, November 29 | 10:20 a.m.-10:30 a.m. | RC608-07 | Room E451BA Swiss team will describe how an artificial intelligence (AI) algorithm can identify acute findings on routine abdominal CT scans, enabling radiologists to prioritize reading of these urgent exams.
October 28, 2018
Algorithm accurately detects changes on chest x-rays
By Erik L. Ridley
Wednesday, November 28 | 11:40 a.m.-11:50 a.m. | SSK05-08 | Room N227BIn this talk, researchers will report that a machine-learning algorithm can perform better than radiologists in detecting changes in findings on serial chest radiographs.
October 28, 2018
Deep learning bolsters interpretation of chest x-rays
By Erik L. Ridley
Wednesday, November 28 | 11:20 a.m.-11:30 a.m. | SSK05-06 | Room N227BResearchers from South Korea will present their deep-learning algorithm for the automatic detection of major thoracic abnormalities on chest radiographs.
October 28, 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 28, 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 28, 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 28, 2018
Machine learning reduces MRI scanning times
By Erik L. Ridley
Tuesday, November 27 | 3:30 p.m.-3:40 p.m. | SSJ18-04 | Room E451BIn this presentation, researchers will show how a machine learning-based image reconstruction algorithm can sharply lower scanning times for brain and lumbar MRI studies.
October 28, 2018
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