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Improved Interpretation of Digitized Mammography with Wavelet Processing: A Localization Response Operating Characteristic Study

¹ All authors: Department of Radiology, College of Medicine, and H. Lee Moffitt Cancer Center and Research Institute at the University of South Florida, 12901 Bruce B. Downs Blvd., Box 17, Tampa, FL 33612-4799.

OBJECTIVE. Our objective was the implementation and evaluation of a novel enhancement technique for improved interpretation of high-resolution digitized mammograms from computer monitors.

MATERIALS AND METHODS. A wavelet algorithm was designed to attenuate the image spectral characteristics responsible for the long-range image correlation that often interferes with digital display. The algorithm was evaluated with a localization response operating characteristic (LROC) experiment with 500 negative, benign, and cancer cases with masses and calcification clusters. Three observers reviewed the original and wavelet-enhanced images on a 5-Mpixel monitor using a custom-made workstation user interface.

RESULTS. Performance indexes were estimated for four different case combinations, each observer, and each interpretation mode. Wavelet enhancement improved the performance of all observers in all case combinations. Detection accuracy ranged from 0.678 to 0.827 for the unprocessed original data and 0.709–0.871 for the enhanced cases. Localization accuracy ranged from 0.547 to 0.785 for the original images and 0.568–0.847 for the enhanced cases, yielding increases of 5–15%. The difference between enhanced and original performances was statistically significant at the 0.10 level and in a few combinations at the 0.05 level.

CONCLUSION. Soft-copy digitized mammography could replace standard film mammography under appropriate display parameters and conditions. The optimization of the soft-copy quality is expected to require more advanced processing techniques than standard gray-scale adjustments. Wavelet-based algorithms, such as the one proposed here, offer better soft-copy quality than the originals and a better starting point for additional manual gray-scale adjustments or automated postprocessing.

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				M. Kallergi, B. J. Lucier, C. G. Berman, M. R. Hersh, J. J. Kim, M. S. Szabunio, and R. A. Clark High-Performance Wavelet Compression for Mammography: Localization Response Operating Characteristic Evaluation Radiology, January 1, 2006; 238(1): 62 - 73. [Abstract] [Full Text] [PDF]