HIGH ACCURACY REGION GROWING SEGMENTATION TECHNIQUE FOR MAGNETIC RESONANCE AND COMPUTED TOMOGRAPHY IMAGES WITH WEAK BOUNDARIES

Segmentation of medical images is challenging due to the poor image contrast and artifacts that result in missing tissue boundaries, i.e. pixels inside the region have similar intensity. In this paper, we introduce a new automatic method for region growing capable to segment 2D/3D Magnetic Resonance Images (MRI) and Computed Tomography (CT) which contain weak boundaries between different tissues. The proposed method is used to extract reliable regions of an image to produce a computer aided design for 3D images. It includes an automatic threshold and is based on estimating probability of pixel intensities of a given image. An automatic threshold is computed as a function of intensity and probability of pixels. This makes the threshold to be flexible and can give large threshold when pixels have very similar intensities and small when they are on the boundaries. The experimental results show that the proposed technique produces accurate and stable results