Video from ISMRM 2019: Jong Chul Ye on machine learning and data reconstruction
May 15, 2019 -- MONTREAL - While most of the focus on machine learning in radiology has been image interpretation, Jong Chul Ye, PhD, of the Korea Advanced Institute of Science and Technology (KAIST) in South Korea believes that data reconstruction is also a fertile area for deep learning. He explains in this video from the International Society for Magnetic Resonance in Medicine (ISMRM) conference.  Discuss
Video from ISMRM 2019: Dr. Hedvig Hricak on disruptors in MRI interpretation
May 14, 2019 -- MONTREAL - Monday morning's talks on disruptors in MRI came to a close with a talk on disruption in the interpretation of MRI data by Dr. Hedvig Hricak, PhD, of Memorial Sloan Kettering Cancer Center. She sees artificial intelligence as having a major potential impact on MRI interpretation, but there are challenges to overcome along the way.  Discuss
Survey assesses worldwide opinion on radiology AI
May 13, 2019 -- Radiologists and radiology residents from the U.S., the Netherlands, Germany, and the Czech Republic have teamed up to launch an online survey designed to gauge how members of the global radiology community view the use of artificial intelligence (AI) in their specialty.  Discuss
Deep-learning software accurately detects ACL tears
May 13, 2019 -- Software based on deep-learning algorithms provided fully automated diagnosis of full-thickness anterior cruciate ligament (ACL) tears on MRI scans at an accuracy level comparable to experienced clinical radiologists, according to research published online May 8 in Radiology: Artificial Intelligence.  Discuss
Deep learning finds, segments brain metastases on MRI
May 10, 2019 -- A deep-learning algorithm automatically detected and segmented brain metastases on multisequence MRI, showing potential to help radiologists and radiation oncologists with these tedious and time-consuming tasks, according to research published online May 2 in the Journal of Magnetic Resonance Imaging.  Discuss
AI finds radiologists vary in follow-up recommendations
May 9, 2019 -- An artificial intelligence (AI) algorithm helped Harvard researchers conclude that radiologists in the same subspecialty division can vary significantly in how often they recommend follow-up imaging examinations, according to an article published online May 7 in Radiology.  Discuss
CT tube voltage doesn't affect AI FFR-CT analysis
May 8, 2019 -- An artificial intelligence (AI) algorithm for estimating fractional flow reserve on coronary CT angiography (FFR-CT) had the same level of performance when used with CT tube voltages of either 100 or 120 kVp, according to research posted online April 30 in the American Journal of Roentgenology.  Discuss
Deep learning enhances breast cancer risk assessment
May 7, 2019 -- By analyzing subtle imaging patterns on screening mammograms that may portend future cancer, a deep-learning algorithm can beat current breast cancer risk-assessment methods that only assess traditional risk factors such as breast density and family history, according to research published online May 7 in Radiology.  Discuss
Radiology is leading by example when it comes to AI
May 1, 2019 -- The radiology community's proactive response to the adoption of artificial intelligence (AI) offers an important lesson to other clinical specialties in how they should prepare for the new era of AI, according to an editorial published online April 25 in the Yearbook of Medical Informatics.  Discuss
Practical considerations of AI: Part 3 -- More AI issues
April 29, 2019 -- Will artificial intelligence (AI) provide better patient care? Almost certainly. Improve radiologist productivity? Without a doubt. But key aspects of AI need to be sorted out, according to part 3 of our series on practical considerations of AI by the PACSman, Michael J. Cannavo.  Discuss