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A New Fast Fractal Modeling Approach for the Detection of Microcalcifications in Mammograms
Journal of Digital Imaging, 08/04/09

Sankar D et al. – The mammograms obtained from The Mammographic Image Analysis Society database (gave a total detection score of 87.6%, 87.6%, 90.5%, and 87.6%, for the conventional and the proposed three methods, respectively.

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Deepa Sankar, 08/05/09

Three fast methods are proposed based on deterministic fractal modeling to detect the presence of microcalcifications (which are early indications of breast cancer) in mammograms are presented in this paper. The disadvantage of conventional fractal coding method is the large amount of time required for encoding. The reduction in encoding time for the proposed methods are obtained by searching for a matching domain, based on mean and variance, dynamic range and mass centre features of the image blocks, instead of searching the entire image. This reduced the encoding time by a factor of 3, 89, and 13, respectively in the three methods with respect to the conventional fractal image coding method with quad tree partitioning. The proposed methods can be effectively used by the radiologists to detect breast cancer when a large number of screening mammograms are to be analyzed.

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