Reconstruction of the human brain from MRI-T1 using 3-d morphology and snake

Abstract

Accurate reconstruction of the human brain in MRI-T1 images is valuable and important to clinical needs. In this paper, the morphology and snake techniques are proposed to reconstruct a human brain model. First step in our method is to preprocess the volumetric image to remove skull, muscle, fat, and other non-brain tissue. We use a method of 3-d region growing. It has the advantage over thresholding that the resulting objects will be spatially connected, since brain has the connected property. Second, we use clustering method, and than use them to produce an initial estimate of the cortical surface. Third, we propose a novel active contour algorithm to move the snake toward the cortex. Thus we can use the snake to segment the brain. We use a wavelet method to model the external force that significantly increases the capture range of a traditional snake. Afterwards, we render the volumetric image to display the brain from multiple views. Both simulated data and patient data have been use to test the proposed techniques. The proposed method combines various techniques of 3-D morphology, clustering, active contour, wavelet, and volume rendering to accurately, robustly, and automatically reconstruct brain from MRI-T1 images.