Abstract
A computer-aided diagnosis (CAD) scheme could improve radiologists' diagnostic performance in their detection of lung nodules on chest radiographs if the computer output were used as a `second opinion'. The current CAD scheme that we have developed achieved a performance of 70% sensitivity and 1.7 false positives per image for our database. This database consisted of two hundred PA chest radiographs, including 100 normals and 100 abnormals (containing 122 confirmed nodules). Our purpose in this study was to improve our scheme further by incorporating new features derived from analysis of the histogram of radial edge gradients on nodule candidates.
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