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The work in this paper examines and criticizes different methods used for prostate tissue classification using trans-rectal ultra-sound (TRUS) images. The suspicious regions are first identified by an accurate region of interest (ROI) identification algorithm. The identified ROIs' are then analyzed using statistical based features as well as spectral based features. For the statistical based features...
This paper presents a new algorithm for prostate texture classification based on transrectal ultrasound (TRUS) images. A Gabor filter is designed to automatically identify the regions of interest (ROI) in the image. Furthermore, texture analysis for these regions is carried out by employing grey level co-occurrence matrix GLCM. Contrast feature is found to be useful for the differentiation between...
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