Comparative Performance Analysis of Segmentation Techniques

The study presented in this article focuses on comparative analysis of Segmentation techniques. Segmentation techniques are applied to extract Region of Interest (ROI) from medical images obtained from different medical scanners such as Ultrasound, CT or MRI. Global thresholding, Adaptive Thresholding, Region grow and Active contour using level set techniques has been used in the proposed segmentation analysis. The approach consists of two steps: Apply segmentation technique to extract most discriminative regions from image and calculate the parameters from the resulting image obtained by the applied techniques. Parameters are precision, accuracy sensitivity, specificity. Segmentation techniques have been tested on medical and synthetic data sets and results are compared with each other. Tests indicate that using level set contour significantly improves the ability of extracting region of interest with unbroken boundaries and Adaptive thresholding acquires most of the details present in the image. Manual global thresholding have the highest success rate of extracting the region of interest.