Vector quantization and signal compression
Vector quantization and signal compression
The nature of statistical learning theory
The nature of statistical learning theory
Polyp Detection in Endoscopic Video Using SVMs
PKDD 2007 Proceedings of the 11th European conference on Principles and Practice of Knowledge Discovery in Databases
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Adenomatous polyps in the colon have a high probability of developing into subsequent colorectal carcinoma, the second leading cause of cancer deaths in United States. In this paper, we propose a new method for computer-aided diagnosis of polyps. Initial work with shape detection has shown high sensitivity for polyp detection, but at a cost of too many false positive detections. We present a statistical approach that uses support vector machines to distinguish the differentiating characteristics of polyps and healthy tissue, and subsequently uses this information for the classification of the new cases. One of the main contributions of the paper is a new 3-D pattern analysis approach, which combines the information from many random images to generate reliable signatures of the shapes. At 80% polyp detection rate, the proposed system reduces the false positive rate by 80% compared to previous work.