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Proceedings Paper

Removal of normal anatomic structures in radiographs using wavelet-based nonlinear variational method for image matching
Author(s): Hiroyuki Yoshida
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Paper Abstract

A wavelet-based image matching method was developed for removal of normal anatomic structures in chest radiographs for reduction of false positives reported by our computer- aided diagnosis (CAD) scheme for detection of lung nodules. In our approach, two regions of interest (ROIs) are extracted, one from the position where a candidate of a nodule is located, and the other from the position located at a point symmetric to the first position relative to the spine. The second ROI contains normal anatomic structures similar to those of the first ROI. A non-linear functional representing the squared differences between the two images is formulated, and is minimized by a coarse-to-fine approach to yield a planar mapping that matches the two similar images. A smoothing term is added to the non-linear functional, which penalizes discontinuous and irregular mappings. If no structure remains in the difference between these matched images, then the first ROI is identified to be a false detection (i.e., it contains only normal structures); otherwise, it is regarded as a nodule (i.e., it contains an abnormal structure). A preliminary result shows that our method is effective in removing normal anatomic structures and thus is useful for substantially reducing the number of false detections in our CAD scheme.

Paper Details

Date Published: 19 October 1998
PDF: 8 pages
Proc. SPIE 3458, Wavelet Applications in Signal and Imaging Processing VI, (19 October 1998); doi: 10.1117/12.328134
Show Author Affiliations
Hiroyuki Yoshida, Univ. of Chicago (United States)

Published in SPIE Proceedings Vol. 3458:
Wavelet Applications in Signal and Imaging Processing VI
Andrew F. Laine; Michael A. Unser; Akram Aldroubi, Editor(s)

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