9 March 2010 An open source implementation of colon CAD in 3D slicer
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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/).
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Haiyong Xu, Haiyong Xu, H. Donald Gage, H. Donald Gage, Pete Santago, Pete Santago, } "An open source implementation of colon CAD in 3D slicer", Proc. SPIE 7624, Medical Imaging 2010: Computer-Aided Diagnosis, 762421 (9 March 2010); doi: 10.1117/12.844370; https://doi.org/10.1117/12.844370

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