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9 May 2002 Enhanced lung cancer detection in temporal subtraction chest radiography using directional edge filtering techniques
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Abstract
We have developed a series of directional edge enhancement and edge extraction methods that can accurately segment posterior and anterior ribs in chest radiography. These methods can also separate the lower and upper edges of ribs. The edges were first enhanced by two sets of proximate parabola curve models for left and right sides of the image. We used a directional edge filtering technique to remove low signals and noises on the edge enhanced image in the multiresolution domain. Finally, we employed a rib curve projection and reasoning method to reconstruct the rib edges and remove false edges for the upper and lower bound of the rib edges independently. A two-step registration, corresponding to global and local matching, is applied for current and prior images assisted by their corresponding edge images. The subtraction images were then processed by a rule-based CAD system. The FROC results were compared to that obtained by the original image using a CAD system consisting of rule-based and convolution neural network processing. The majority of lung cancer in temporal subtraction images were lit-up. The FROC results were significantly improved using the subtraction image with the rule-based CAD.
© (2002) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Hui Zhao, Shih-Chung Benedict Lo, Matthew T. Freedman M.D., and Yue Joseph Wang "Enhanced lung cancer detection in temporal subtraction chest radiography using directional edge filtering techniques", Proc. SPIE 4684, Medical Imaging 2002: Image Processing, (9 May 2002); https://doi.org/10.1117/12.467212
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