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Proceedings Paper

Application of weighted-majority minimum-range filters in the detection and sizing of tumors in mammograms
Author(s): Lucille Amy Glatt; Harold G. Longbotham; Thomas L. Arnow; Daniel Shelton; Peter Ravdin
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Paper Abstract

In image processing the solution is often unique to the problem. To be more specific, the importance of the filter window and sampling pattern chosen to filter, pass, or enhance a specific shape is very specific to the problem at hand. We detect suspect tumors in mammograms using a weighted majority minimum range filter and different sampling patterns and windows as a demonstration of this fact. Several methods have been developed to automate the process of detecting tumors in mammograms. We show that traditional windowing or sampling methods may be replaced by a hexagonal method that more accurately reflects the geometry of the problem and could improve the techniques already in existence. Several theorems involving a hexagonal filter window are presented, followed by the results of our application to mammograms.

Paper Details

Date Published: 1 June 1992
PDF: 12 pages
Proc. SPIE 1652, Medical Imaging VI: Image Processing, (1 June 1992); doi: 10.1117/12.59457
Show Author Affiliations
Lucille Amy Glatt, Univ. of Texas/San Antonio (United States)
Harold G. Longbotham, Univ. of Texas/San Antonio (United States)
Thomas L. Arnow, Univ. of Texas/San Antonio (United States)
Daniel Shelton, Univ. of Texas/San Antonio (United States)
Peter Ravdin, Univ. of Texas Health Science Ctr./San Antonio (United States)

Published in SPIE Proceedings Vol. 1652:
Medical Imaging VI: Image Processing
Murray H. Loew, Editor(s)

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