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Tissue Characterization in Prostatic Lesion Using Statistical Feature Analysis
Abstract
The early detection of prostate cancer plays a significant role in the success of treatment and outcome. Trans Rectal Ultra-Sound (TRUS) is one of the most common non invasive diagnostic imaging method enable objective judgments by making use of quantitative measures. In this paper, we present a novel approach to statistically characterize the prostate tissue into different regions as malignant, prostatic calculi, presence of cyst, normal prostate. The characterization of the tissue involves two parts. The first part is to, automatically, segment the prostate gland and to detect the regions, which might be cancerous, for biopsies. The second part is to extract the ROI and to characterize the regions as malignant based on the statistical features obtained from the histogram of the prostate images. After the characterization the performance of this method is estimated by comparing the statistical parameters such as sensitivity, specificity, accuracy with the biopsy result.
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References
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