A False Positive Reduction in Mass Detection Approach using Spatial Diversity Analysis

Efforts in image processing and pattern recognition have been made in order to help improving the detection accuracy by physicians. In this paper, we present a analysis that study the use of Diversity Indexes in a Spatial approach as a texture measure in order to distinguish suspicious regions previously detected by segmentation scheme. The description of the pattern is based on the fact that the important features could be distributed on the region under certain distance, angle and tonalities. And these tonalities represents species that have a particular associations that may be important distinctions between the pattern of mass and non-mass regions helping do false positive reduction and assisting a physician on a task of verify suspicious regions on a mammogram. The computed measures are classified through a Support Vector Machine and reaches a reduction of 75% of false positives on mass detection methodology. Keywords-Mass False Positive Reduction; Pattern Recognition; Diversity Index.

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