Branch-based Region Growing Method for Blood Vessel Segmentation

We propose an algorithm of blood vessel segmentation for MRA data in this paper. The generic region growing, as well as thresholding, is not appropriate to extract the whole part of the vessels on MRA data. This is because of the image property of the MRA, where the intensity of each pixel on the blood area depends on the amount of blood flow. Moreover, thin vessels are affected by the partial volume effect which reduces the intensity of vessel parts as the low pass filtering effect. So the range of the intensity of the blood vessel in MRA image is not restricted in a small interval but spread widely. To get correct segmentation results by region growing, the growing condition should be flexibly adapted according to the local characteristics in each ROI. We have designed a branch-based region growing for this purpose. Since its growing process is performed on one branch at a time, the growing conditions can be optimized according to its surrounding properties. It is also possible to connect a break point by extending the vessel, which improves segmentation results. By applying this method to 5 head MRA data sets, the availability of the method has been confirmed. In addition, to evaluate the segmentation result quantitatively, we developed a new evaluation method which utilizes MIP data.