In cerebrovascular disorder diagnosis computer-aided diagnosis of intracranial aneurysms, segmenting of high-intensity major vessels along with the low-contrast aneurysms is essential to the recognition of lethal vascular disease. This paper proposes a novel intensity-based algorithm to segment intracranial vessels and the attached aneurysms. The proposed method can handle intensity varying vasculatures and also the low-contrast aneurysmal regions affected by turbulent flows. It is grounded on the use of multi range filters and local variances to extract intensity-based image features for identifying contrast varying vasculatures. The extremely low-intensity region affected by turbulent flows is detected according to the topology of the structure detected by multi range filters and local variances. The proposed method is evaluated using a phantom image volume with an aneurysm and four clinical cases. Owing to the analogy between these variants and existing vascular segmentation methods, this comparison also exemplifies the advantage of the proposed method over the existing approaches.