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16 April 1996 Use of texture analysis and boundary refinement to delineate suspicious masses in mammography
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Abstract
Texture analysis using convolution filters has been proposed as a method for the quantitation of extended objects in mammography. The work reported incorporates additional steps of image processing in an attempt to improve the performance of these filters. By deriving approximate outlines which are used to identify suspicious regions, the investigation illustrates the properties of one of the filters. After applying the method to a small pre-diagnosed database of stellate lesions and regular masses, the results show that the filter is able to outline the masses in all cases presented. The erroneous areas extracted are small for the initial part of the work which deals with 256 by 256 pixel image extracts, though slightly larger in some cases when the whole mammogram is considered. For each non-suspicious case studied, the sum of any false positive areas is statistically small when compared with the regions correctly outlined in the pre-diagnosed instances. By using an active contour model the outline match has been improved for the regular masses and also, but to a lesser degree, for the stellate lesions.
© (1996) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Peter E. Undrill, Ramyani Gupta, Sonia Henry, and Martin J. Downing "Use of texture analysis and boundary refinement to delineate suspicious masses in mammography", Proc. SPIE 2710, Medical Imaging 1996: Image Processing, (16 April 1996); https://doi.org/10.1117/12.237933
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