VIRTUAL COLONOSCOPY VIA WAVELETS

Various techniques can be used to improve classification of colon polyps candidates found via computed tomographic colonography computer aided detection (CTCCAD). A polyp candidate can be classified as a true positive or a false positive. For example, a two-dimensional projection image of the polyp can be generated from a three-dimensional representation and classified based on features of the projection image. An optimal viewpoint for the projection image can be found via techniques such as maximizing viewpoint entropy. Wavelet processing can be used to extract features from the two-dimensional projection image. Feature extraction can use a piecewise linear orthonormal floating search for locating most predictive neighbors for wavelet coefficients, and support vector machines can be employed for classification. The techniques can be useful for improving accuracy of CTCCAD techniques.