Erik L. Ridley[email protected]ISCT dose excellence program yields optimized doseMonday, November 27 | 12:15 p.m.-12:45 p.m. | QS110-ED-MOA2 | Lakeside, QS Community, Station 2A Swiss team will describe how it successfully implemented an initiative to standardize CT scanning protocols and optimize radiation dose.October 29, 2017ISRadiology must address cybersecurity challengesMonday, November 27 | 11:50 a.m.-12:00 p.m. | SSC08-09 | Room S402ABThis keynote talk will highlight the considerable cybersecurity threat facing radiology departments and emphasize the importance of encryption in defending against future attacks.October 29, 2017ISData mining may help spot patients with fracture riskMonday, November 27 | 11:20 a.m.-11:30 a.m. | SSC09-06 | Room E450BIn this scientific presentation, researchers from Switzerland will share how their PACS data-mining software shows potential for identifying patients at risk of osteoporotic fractures.October 29, 2017ISDose tracking software finds CTA won't harm fetusesSunday, November 26 | 12:05 p.m.-12:15 p.m. | SSA06-09 | Room N226German researchers using radiation dose management and tracking software have found that pulmonary CT angiography (CTA) is safe to perform during pregnancy.October 29, 2017MRIDeep learning can enable quantitative MRI for arthritisA deep-learning algorithm can accurately segment knee MRI scans and extract quantitative data in seconds, potentially helping radiologists to easily provide clinicians with valuable data for diagnosing, assessing, and treating osteoarthritis, according to a team from the University of California, San Francisco.October 15, 2017Advanced Visualization3D-printed model helps prepare for stroke clot removalA 3D-printed brain perfusion phantom can be a useful tool for interventional radiologists, neurosurgeons, and neuroradiologists to practice performing mechanical thrombectomy for interventional treatment of stroke, according to a team from the University of Connecticut Health Center in Farmington, CT.October 5, 2017CTAI gives one-stop shopping for urinary stone evaluationAn artificial intelligence (AI) algorithm can accurately detect and classify urinary stones based solely on images from noncontrast single-energy CT scans, according to research presented at last week's Society for Imaging Informatics in Medicine's Conference on Machine Intelligence in Medical Imaging.October 4, 2017Advanced VisualizationAuntMinnie.com Advanced Visualization InsiderOctober 3, 2017AIAuntMinnie.com Artificial Intelligence InsiderOctober 2, 2017PACS/VNAAuntMinnie.com Imaging Informatics InsiderSeptember 27, 2017Previous PagePage 113 of 389Next PageTop StoriesInterventionalWhat’s the best treatment for 'eloquent' brain AVMs?Researchers performed the first direct comparisons of two emerging techniques for treating arteriovenous malformations (AVMs).Womens ImagingPreop MRI lessens younger women's risk of breast cancer recurrenceMRIMRI predicts diabetes in obese patientsCTConsider global lung features on LDCT to improve cancer risk predictionSponsor ContentJoin Us!