Resources: Page 467

Using 3D in patients with penetrating trauma
By Erik L. Ridley
Education Exhibit | LL-ERE2249 | Lakeside Learning CenterVisitors to this exhibit in the Lakeside Learning Center will learn how 3D postprocessing imaging techniques can assist in trauma-related patient care.
November 14, 2010
CAD system can quantify multiple sclerosis lesions
By Erik L. Ridley
Thursday, December 2 | 12:15 p.m.-12:45 p.m. | LL-INS-TH1A | Lakeside Learning CenterIn this poster presentation, researchers from the University of Southern California Keck School of Medicine in Los Angeles will discuss developments with their multiple sclerosis lesion computer-aided detection (CAD) algorithm.
November 14, 2010
Visual search patterns of volumetric datasets may reveal much
By Erik L. Ridley
Thursday, December 2 | 11:20 a.m.-11:30 a.m. | SSQ10-06 | Room S402ABResearchers from Stanford University in Stanford, CA, will share their work in this Thursday session on investigating the perceptual capabilities of the human visual system in relation to medical images.
November 14, 2010
Using VC CAD as second reader performs best
By Erik L. Ridley
Thursday, December 2 | 11:20 a.m.-11:30 a.m. | SSQ05-06 | Room E353CIn this paper presentation, researchers will share their findings from evaluating different reading methods for virtual colonoscopy computer-aided detection (CAD) by experienced readers.
November 14, 2010
Using VC CAD as first reader offers efficiency gains
By Erik L. Ridley
Thursday, December 2 | 11:10 a.m.-11:20 a.m. | SSQ05-05 | Room E353CIn this scientific session, a study team from Italy will discuss how the use of virtual colonoscopy computer-aided detection (CAD) as a first reader can reduce reading times without sacrificing performance.
November 14, 2010
VC CAD can be used with, without fecal tagging
By Erik L. Ridley
Thursday, December 2 | 11:00 a.m.-11:10 a.m. | SSQ05-04 | Room E353CA research group will present data that showed no significant performance difference in employing virtual colonoscopy computer-aided detection (CAD) on patients with or without fecal tagging.
November 14, 2010
Advanced visualization method slashes VC interpretation times
By Erik L. Ridley
Thursday, December 2 | 10:50 a.m.-11:00 a.m. | SSQ05-03 | Room E353CIn this paper presentation, a German team will share how a new 3D visualization technique can provide fast and accurate interpretation of virtual colonoscopy images.
November 14, 2010
Can facial recognition software identify patients based on 3D facial images?
By Erik L. Ridley
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, 2010
iPad offers potential in radiology
By Erik L. Ridley
Wednesday, 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, 2010
Elastography CAD application equals radiologist interpretation
By Brian Casey
Wednesday, December 1 | 11:20 a.m.-11:30 a.m. | SSK12-06 | Room N229In a positive early finding, South Korean researchers found that the use of a computer-aided detection (CAD) algorithm to generate ultrasound elasticity scores in thyroid scans worked as well as radiologists generating the scores on their own.
November 14, 2010
Concurrent use of CAD fares well in low-dose CT
By Erik L. Ridley
Wednesday, 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, 2010
Automatic segmentation algorithm yields workflow gains
By Erik L. Ridley
Tuesday, 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, 2010
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