A growing body of evidence suggests that there is a strong association between neurodegenerative diseases such as Alzheimer's Diseases and the abnormality of the cerebral vasculature, in particular the microvessels/capillaries that are responsible for the exchange of nutrients across the blood-brain barrier [1]. Many microvessels are described as being kinked or distorted [2], implying that they are modified by some destructive process. Imaging devices such as microCT can achieve resolutions on the order of several µm, allowing imaging the three dimensional (3D) microvasculature down to the capillary level. However, the main weakness of using microCT for vascular research is considered to be the lack of software for 3D quantification of microvasculature and microvascular image databases for developing and testing algorithms. In this paper we describe a multifractal analysis method for the microvasculature automatically segmented from microCT images of the mouse brain. Due to the lack of a benchmark microCT image database, the method has been tested using a surrogate database--a publicly available retinal vessel database. The results are preliminary indication of the multifractal properties of mouse brain vasculature. A potential solution to automated classification of healthy and disease brains are discussed.