Erik Ridley

Erik is senior editor at AuntMinnie.com and focuses on coverage of artificial intelligence and imaging informatics. He joined the website in 2000 and has 24 years of radiology journalism experience, including previous stints with Diagnostic Imaging magazine, Diagnostic Imaging Scan newsletter, and PACS and Networking News. Erik holds a bachelor's degree in journalism from the University of Connecticut.

Articles by this author
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
ARRS: PACS upgrade slashes image reading time
May 6, 2019 -- Sometimes, little things make a big difference. Pennsylvania researchers improved the efficiency of their radiologists by tweaking their PACS software to look for prior imaging exams with more specific search criteria, according to research presented at the American Roentgen Ray Society (ARRS) annual meeting in Honolulu.  Discuss
AI model could enable gadolinium-free cardiac MRI
May 2, 2019 -- Researchers developed an artificial intelligence (AI) algorithm that accurately detected chronic myocardial infarction on noncontrast-enhanced cardiac cine MRI, potentially obviating the need for gadolinium-based contrast agents in these patients, according to research published online April 30 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
Can radiomics detect pancreatic ductal adenocarcinoma?
April 25, 2019 -- Radiomics and a machine-learning algorithm can differentiate pancreatic ductal adenocarcinoma from a normal pancreas on CT studies, potentially enabling earlier diagnosis of this highly lethal cancer, according to research published online April 23 in the American Journal of Roentgenology.  Discuss
AI can identify, classify prostate cancer on mpMRI
April 18, 2019 -- An artificial intelligence (AI) algorithm called FocalNet was able to identify prostate cancer on multiparametric MRI (mpMRI) nearly as well as experienced radiologists and also predicted the lesion's aggressiveness, according to research presented at the recent IEEE International Symposium on Biomedical Imaging in Venice, Italy.  Discuss