A robust segmentation algorithm for branch structure and its implementation

Medical image segmentation is a serious challenge in medical image processing. The medical images have low contrast, the variability of the organizational characteristics, the ambiguity of the border of the tissues and the complexity of microstructures (e.g. blood vessels, nerves). These features restrict the segmentation of the branch structure in the medical images. This paper presents a robust medical segmentation algorithm that combines the active contour model and region growth segmentation method. General locations, given by the region growth segmentation method, act as the initial position of snake model for segmentation. In this way, we can get the branch structure in the abdominal CT, such as the abdominal aorta, the celiac trunk and mesenteric artery. The experimental result shows that the revised algorithm achieves a better practical effect through surface rendering from VTK. It can help the doctor diagnose the illness wisely and objectively.