
Proceedings Paper
An open source implementation of colon CAD in 3D slicerFormat | Member Price | Non-Member Price |
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Paper Abstract
Most colon CAD (computer aided detection) software products, especially commercial products, are designed for use by
radiologists in a clinical environment. Therefore, those features that effectively assist radiologists in finding polyps are
emphasized in those tools. However, colon CAD researchers, many of whom are engineers or computer scientists, are
working with CT studies in which polyps have already been identified using CT Colonography (CTC) and/or optical
colonoscopy (OC). Their goal is to utilize that data to design a computer system that will identify all true polyps with no
false positive detections. Therefore, they are more concerned with how to reduce false positives and to understand the
behavior of the system than how to find polyps. Thus, colon CAD researchers have different requirements for tools not
found in current CAD software. We have implemented a module in 3D Slicer to assist these researchers. As with clinical
colon CAD implementations, the ability to promptly locate a polyp candidate in a 2D slice image and on a 3D colon
surface is essential for researchers. Our software provides this capability, and uniquely, for each polyp candidate, the
prediction value from a classifier is shown next to the 3D view of the polyp candidate, as well as its CTC/OC finding.
This capability makes it easier to study each false positive detection and identify its causes. We describe features in our
colon CAD system that meets researchers' specific requirements. Our system uses an open source implementation of a
3D Slicer module, and the software is available to the pubic for use and for extension
(http://www2.wfubmc.edu/ctc/download/).
Paper Details
Date Published: 9 March 2010
PDF: 9 pages
Proc. SPIE 7624, Medical Imaging 2010: Computer-Aided Diagnosis, 762421 (9 March 2010); doi: 10.1117/12.844370
Published in SPIE Proceedings Vol. 7624:
Medical Imaging 2010: Computer-Aided Diagnosis
Nico Karssemeijer; Ronald M. Summers, Editor(s)
PDF: 9 pages
Proc. SPIE 7624, Medical Imaging 2010: Computer-Aided Diagnosis, 762421 (9 March 2010); doi: 10.1117/12.844370
Show Author Affiliations
Haiyong Xu, Wake Forest Univ. (United States)
Virginia Tech - Wake Forest Univ. (United States)
H. Donald Gage, Wake Forest Univ. (United States)
Virginia Tech - Wake Forest Univ. (United States)
Virginia Tech - Wake Forest Univ. (United States)
H. Donald Gage, Wake Forest Univ. (United States)
Virginia Tech - Wake Forest Univ. (United States)
Published in SPIE Proceedings Vol. 7624:
Medical Imaging 2010: Computer-Aided Diagnosis
Nico Karssemeijer; Ronald M. Summers, Editor(s)
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