Abstract
For some biomedical purpose, a specific region needs to be extracted from a target 3-D image stack which usually consists of many 2-D slices. In previous work, a template-driven segmentation scheme by using snake is presented to find the approximate outline and position of the specific region on each slice of the target image stack based on the template (reference) 3-D image stack.In this thesis, a modified auto-segmentation process will be proposed. A ROI-finding scheme and a texture-based segmentation algorithm are used to avoid the original drawbacks. There are mainly four stages presented in this thesis to achieve the refinement: (i) ROI (region of interest)—finding process is used to filter out unnecessary area and locate the specific region. (ii) Texture-based multi-resolution segmentation scheme is used to segment target images by using local spectral histogram. (iii) Volume-smoothing method is used to smooth segmentation mask of each slice along depth-axis. (iv) Morphology is used to make the suggested contour much smoother.This process is more efficient than extracting the specific region by hand. Moreover, the problem of the blurred edges in the specific region is also addressed.