Dear Advanced Visualization Insider,
Advanced visualization technology has shown real clinical utility in the face of today's increasingly large image datasets. But those benefits come with a number of difficult workflow and integration challenges, according to Dr. Paul J. Chang of the University of Chicago Pritzker School of Medicine.
As the number of near-isotropic image datasets increases year after year, institutions are facing a serious data management and informatics challenge, according to Chang.
Chang spoke about the workflow and infrastructure for tackling large image datasets at the March Digital Healthcare Information Management Systems (DHIMS) 2008 meeting in San Antonio, sponsored by the University of Rochester School of Medicine and Dentistry in Rochester, NY.
His presentation is the subject of this month's Insider Exclusive article. You have access to the story before it is published for the rest of our AuntMinnie.com members. To learn more about how to handle the challenges associated with advanced visualization and large image datasets, click here.
Among other articles in our Advanced Visualization Digital Community, a recent study found the sensitivity of computer-aided detection (CAD) algorithms varied depending on the criteria used to evaluate the location of a mark on a suspicious finding. For that story, click here.
In another study, colon CAD turned in strong results for identifying flat polyps that readers might miss on virtual colonoscopy. You'll find that story here. Also, a pair of presentations revealed mixed benefits in the use of CAD for detecting lung nodules in thoracic exams. Get the details here.
