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30 October 1997 Wavelet-based deformable contour and its application to detection of pulmonary nodules on chest radiographs
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A wavelet-based deformable contour called the wavelet snake has been developed, and applied to distinction of tumors from false detections reported by our computer-aided diagnosis (CAD) scheme for detection of pulmonary nodules in digital chest radiographs. In this technique, multiscale edge representation using spline wavelets was employed as a preprocessing step for extraction of an approximate boundary of a candidate nodule in each region of interest (ROI) reported by our CAD scheme. These multiscale edges are then used to `guide' the wavelet snake to estimate the true boundary of the nodule. The wavelet snake is designed to deform its shape based on a maximum a posteriori estimation performed by a gradient descent algorithm. The degree of overlap between the resulting snake and the multiscale edges were calculated at two scales, and a combination of the overlap measures at these scales were used as a measure for distinction between the ROIs containing nodules and non- nodules. A set of ROIs consisting of 94 nodules and 518 false positives were used for evaluation of our method by means of the receiver operating characteristic (ROC) analysis. Our method yielded an area under the ROC curve of 0.79 in classification performance, which reduced 19% of the false positives with sacrifice of only one nodule.
© (1997) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Hiroyuki Yoshida, Shigehiko Katsuragawa, Yali Amit, and Kunio Doi "Wavelet-based deformable contour and its application to detection of pulmonary nodules on chest radiographs", Proc. SPIE 3169, Wavelet Applications in Signal and Image Processing V, (30 October 1997);

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