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Proceedings Paper

Local contralateral subtraction based on simultaneous segmentation and registration method for computerized detection of pulmonary nodules
Author(s): Hiroyuki Yoshida
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Paper Abstract

Many of the existing computer-aided diagnosis (CAD) schemes for detection of nodules in chest radiographs suffer from a large number of false positives. Previously, we reported a local contralateral subtraction method that removes false positives due to the presence of normal structures effectively. In this approach, registration of the left and right lung regions is performed for extraction of lung nodules while the normal anatomic structures are removed. In this study, we developed a novel method for simultaneous registration and segmentation which registers two similar images while a region with significant difference is adaptively segmented, and incorporated it into the local contralateral subtraction method. In this method, a non- linear functional that models the statistical properties of the subtraction of the two images is formulated, and the function is minimized by a coarse-to-fine approach to yield a mapping that yields the registration and a boundary that yields the segmentation. A preliminary result shows that the new method is effective in segmenting the abnormal structures and removing normal structures. The local contralateral subtraction based on the new segmentation and registration method was shown to be effective in reducing the number of false detections reported by our computer- aided diagnosis scheme for detection of lung nodules in chest radiographs.

Paper Details

Date Published: 3 July 2001
PDF: 5 pages
Proc. SPIE 4322, Medical Imaging 2001: Image Processing, (3 July 2001); doi: 10.1117/12.431114
Show Author Affiliations
Hiroyuki Yoshida, Univ. of Chicago (United States)


Published in SPIE Proceedings Vol. 4322:
Medical Imaging 2001: Image Processing
Milan Sonka; Kenneth M. Hanson, Editor(s)

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