Prostate TRUS Image Region-Based Feature Extraction and Evaluation
In this work a new informative feature set is proposed to identify suspicious Regions Of Interest (ROIs) in the prostate TransRectal UltraSound (TRUS) images. The proposed features are region based to overcome the limitations present in the pixel based feature extraction methods. First a thresholding algorithm integrated with the medical information is used to identify different candidate ROIs. Next, image registration is performed to transform the prostate image to a model based from which some of the proposed region based features are extracted. Subsequently, the proposed raw based and model based region features are extracted at the region level.
Finally Mutual Information is used to evaluate the extracted features and compare their information content with both the typical pixel based features and the well known texture and grey level features. It was found that the proposed features provide more information than both the texture features and the pixel based features.
Keywordsfeature extraction region-based features mutual information symmetry measure TRUS
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