Fuzzy Information Granulation of Medical Images. Blood Vessel Extraction from 3-D MRA Images

Abstract

Along with the population of high field magnetic resonance imaging (MRI), MR angiography (MRA) imaging with no contrast is rapidly gaining acceptance as a versatile noninvasive alternative to the conventional MRA with contrast and the CT angiography (CTA). To construct the volume visualizations of the cerebral blood vessels from volumetric MRA images of the brain, maximum intensity projection (MIP) technique has been widely used by many physicians [1]. The MIP image is created by selecting the maximum value along on an optical ray corresponding to each pixel of the image. The technique and the mutations have some advantages. For example, it gives densitometric information of raw images without any parameters needing to be tuned, and its implementation is relatively simple [1][2]. However, it also contains critical limitations. They are that it cannot depict the spatial relationship of overlapping vessels, and large bright structures may disturb region of interests (ROIs) along on optical rays from both directions. Some studies investigated the advantages and the disadvantages of three visualization techniques, i.e. MIP, volume rendering (VR), and surface shaded display (SSD) [3][4]. They concluded that SSD is useful to evaluating overlapping vessels, and it provides a better definition of the aneurysm neck and the morphology of saccular aneurysms. However, SSD is not used widely today because there is no application to automatically segment the blood vessel region. To construct the SSD images, a user must manually segment the blood vessel