The Detection Of Calcification Clusters In Film-Screen Mammograms; A Detailed Algorithmic Approach

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Abstract
An efficient algorithm has been developed for the detection of clustered micro-calcifications in digitized film-screen mammograms. The calcification cluster detection algorithm involves a decision-theoretic mechanism which identifies calcifications meeting specific size, density, and clustering criteria. The algorithm first utilizes a pixel testing and region grouping procedure to identify pixels with specific intensity characteristics. A region growing procedure is then applied to identify pixels belonging to contiguous structures. Each single- and multi-pixel structure is subsequently tested against criteria for size, shape, contrast, and intensity to determine if the composite structure matches the expected characteristics of mammographic calcifications. Detected calcifications are then tested to determine if they fall within a cluster meeting specific density constraints. Only calcifications located in such clusters are marked in the processed image. This algorithmic process has been applied to mammograms from 40 clinical cases in which a biopsy was performed based on the presence of suspicious calcifications. The algorithm accurately identified the suspicious calcifications in each situation; in several cases, it also detected other clusters which were so fine as not to be visible in clinical screening.© (1988) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.
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