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Proceedings Paper

Integer wavelet compression guided by a computer-aided detection system in mammography
Author(s): Shih-Chung Benedict Lo; Erini Makariou; Andrzej Delegacz; Heang-Ping Chan; Donald D. Dorfman; Matthew T. Freedman; Kevin S. Berbaum
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Paper Abstract

Since an image data compression technique is usually associated with a low-pass filter, the unsharpness of calcifications and edges are of clinical concerns in mammography. The same effect may turn film defects into calcification-like spots and could produce false-positive detection by the radiologist. In this study, we employed a highly sensitive calcification detection system to guide an S+P integer wavelet compression, so that the data fidelity of calcifications or unknown spots are fully preserved. The prediction component of the S+P decomposition is based on Daubechies'D8. Our results indicated that the modified CAD program detected an average of 1,193 potential calcifications on CC view mammograms and an average of 948 potential calcifications on MLO view mammograms, respectively. Compressed data rates between 0.1 to 0.43 bit/pixel were studied. The compressed images were evaluated by subjective comparison studies. The results indicated that no difference could be observed between the original and the 0.43 bit rate decompressed images. The radiologist identifies 20% of the compressed images at 0.1 bit rate suffering from minor blurry artifacts and 6% of the compressed images possessing greater edge sharpness. Without a lossless compression for microcalcifications, the radiologist identified 20% of the microcalcifications on the compressed mammograms at 0.1 bit rate suffering from minor compression artifacts.

Paper Details

Date Published: 3 July 2001
PDF: 6 pages
Proc. SPIE 4322, Medical Imaging 2001: Image Processing, (3 July 2001); doi: 10.1117/12.431138
Show Author Affiliations
Shih-Chung Benedict Lo, Georgetown Univ. Medical Ctr. (United States)
Erini Makariou, Georgetown Univ. Medical Ctr. (United States)
Andrzej Delegacz, Georgetown Univ. Medical Ctr. (United States)
Heang-Ping Chan, Univ. of Michigan (United States)
Donald D. Dorfman, Univ. of Iowa (United States)
Matthew T. Freedman, Georgetown Univ. Medical Ctr. (United States)
Kevin S. Berbaum, Univ. of Iowa (United States)


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

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