Erik L. Ridley[email protected]CTAI can improve reproducibility of radiomics in CTAn artificial intelligence (AI) algorithm may be able to help overcome one of the biggest issues limiting the clinical use of radiomics in CT -- the low reproducibility of quantitative imaging features on images from different reconstruction algorithms, according to research published online June 18 in Radiology.June 23, 2019BreastAI enhances diagnostic performance in mammographyAn artificial intelligence (AI) algorithm that analyzes mammograms and patient clinical information in electronic health records can accurately diagnose breast cancer -- even in many cases in which cancers are missed by radiologists, according to research published online June 18 in Radiology.June 19, 2019AIAuntMinnie.com Artificial Intelligence InsiderJune 16, 2019PACS/VNACDs still prevail for giving patients access to imagesThe compact disk (CD) has increasingly become an obsolete form of storage that's no longer readily accessible by many computers. However, most hospitals still rely on this archaic medium to provide patients with copies of their imaging studies, according to research published online June 11 in Radiology.June 12, 2019CTAI converts low-dose CT scans to high-quality studiesAn artificial intelligence (AI) algorithm can transform low-dose CT (LDCT) scans into high-quality exams that radiologists may even prefer over LDCT studies produced via commercial iterative reconstruction techniques, according to research published online June 10 in Nature Machine Intelligence.June 11, 2019AIDeep learning helps detect intracranial aneurysmsA deep-learning algorithm called HeadXNet can improve the performance of clinicians of varied specialties and levels of experience for detecting intracranial aneurysms on head CT angiography exams, according to research published online June 7 in JAMA Network Open.June 9, 2019AI6 ways AI will enhance musculoskeletal imagingArtificial intelligence (AI) is poised to greatly improve all aspects of the musculoskeletal imaging chain, helping radiology practices be more efficient while still maintaining accuracy and report quality, according to an article published online June 5 in the American Journal of Roentgenology.June 6, 2019AICAD software helps stratify risk in lung cancer patientsBy measuring the percentage of pulmonary fibrosis on CT exams in lung cancer patients, computer-aided detection (CAD) software can also detect and quantify the extent of interstitial lung abnormalities and help in risk stratification of these patients, according to research published online June 4 in Radiology.June 5, 2019BreastAI can trim mammography workload for radiologistsAn artificial intelligence (AI) algorithm can sharply decrease the number of mammograms that require interpretation by radiologists -- without affecting diagnostic accuracy, according to research published online May 30 in the Journal of the American College of Radiology.June 3, 2019BreastAI may help reduce overdiagnosis of breast cancerUtilizing both clinical and imaging data, a risk-assessment model based on artificial intelligence (AI) called the Breast Cancer Risk Calculator could avoid many unnecessary biopsies in patients with BI-RADS 4 mammography findings, according to research published online May 29 in JCO Clinical Cancer Informatics.May 30, 2019Previous PagePage 78 of 389Next PageTop StoriesAIU.S. FDA may need to clarify SaMD validation standardsIn a video interview, a Dana-Farber Cancer Institute expert describes what the "rigor spectrum" is in validation study designs.Molecular ImagingPSMA-PET/CT may replace NaF-PET/CT in advanced prostate cancerWomens ImagingPreop breast MRI improves surgical planning, but use disparities remainWomens ImagingFIGO classification from MRI leads to moderate agreement among radsSponsor ContentRegister Now: Breaking Barriers in Breast Imaging Webinar
