Erik L. Ridley[email protected]PACS/VNACan facial recognition software identify patients based on 3D facial images?Thursday, December 2 | 10:50 a.m.-11:00 a.m. | SSQ10-03 | Room S402ABResearchers from Weill Cornell Medical College in New York City examined the potential for facial recognition software to match patient photos with their 3D images, in this study to be presented on Thursday.November 14, 2010PACS/VNAiPad offers potential in radiologyWednesday, December 1 | 12:45 p.m.-1:15 p.m. | LL-INS-WE1B | Lakeside Learning CenterResearchers from Nassau University Medical Center in East Meadow, NY, will examine in this poster presentation how the iPad might aid radiology.November 14, 2010CTConcurrent use of CAD fares well in low-dose CTWednesday, December 1 | 10:40 a.m.-10:50 a.m. | SSK05-02 | Room S404CDWhat are the effects of running a computer-aided detection (CAD) algorithm concurrently during the reading process for low-dose CT studies? A group from Kobe University in Japan sought answers in this study.November 14, 2010Image ProcessingAutomatic segmentation algorithm yields workflow gainsTuesday, November 30 | 3:20 p.m.-3:30 p.m. | SSJ14-03 | Room S402ABResearchers from software giant Microsoft of Redmond, WA, will show an automated full-body CT segmentation algorithm that can provide access to quantitative information, among other benefits.November 14, 2010CTVC CAD helps radiologists detect difficult polypsTuesday, November 30 | 11:50 a.m.-12:00 p.m. | SSG13-09 | Room S403AIn another presentation from the University of Chicago, researchers will show how virtual colonoscopy computer-aided detection (CAD) software can assist in identifying difficult polyps.November 14, 2010CTNew VC CAD technique powers up sensitivity for flat lesionsTuesday, November 30 | 11:30 a.m.-11:40 a.m. | SSG13-07 | Room S403AIn this Tuesday paper presentation, a University of Chicago team will share its results with a new computer-aided detection (CAD) technique that may yield higher sensitivity for the all-important flat lesions found on virtual colonoscopy.November 14, 2010BreastCAD aids in assessing breast amorphous calcificationsTuesday, November 30 | 11:30 a.m.-11:40 a.m. | SSG01-07 | Room E450AIn this session, researchers from Princess Margaret Hospital in Toronto will present data showing a high sensitivity for computer-aided detection (CAD) technology in detecting amorphous calcifications on full-field digital mammography studies.November 14, 2010Image ProcessingAutomatic segmentation technique shows promise for CT urogramsTuesday, November 30 | 11:20 a.m.-11:30 a.m. | SSG13-06 | Room S403AResearchers from the University of Michigan in Ann Arbor have developed an automatic bladder lesion segmentation technique for CT urograms. Presenter Lubomir Hadjiiski, PhD, will share the details of their study in this session on Tuesday.November 14, 2010UltrasoundInteractive breast ultrasound CAD improves lesion characterizationTuesday, November 30 | 11:10 a.m.-11:20 a.m. | SSG01-05 | Room E450AIn this Tuesday scientific session, a Canadian research team will share details on why computer-aided detection (CAD) can be a useful adjunctive tool for interpreting breast ultrasound studies.November 14, 2010CTNew CAD approach reduces false-positives for HCCTuesday, November 30 | 10:30 a.m.-10:40 a.m. | SSG13-01 | Room S403AA University of Chicago team will provide an update on its development of computer-aided detection (CAD) software for addressing hepatocellular carcinoma (HCC), according to this paper to be presented on Tuesday morning.November 14, 2010Previous PagePage 234 of 393Next PageTop StoriesCTUsing GPT‑4o with CT exams helps diagnose ovarian cancer earlierEarly detection of ovarian cancer is a persistent challenge, with more than half still diagnosed at metastatic stages.Womens ImagingSurvey: Nearly 4 out of 5 practices short on breast imagersRadiation Oncology/TherapyPooled evidence: Lu-177 PSMA-617 vs. established therapies in mCRPCMRICardiac MRI-based ML model predicts MACE risk for STEMI patientsSponsor ContentHow Agentic AI Is Transforming Radiology Ops
