Cerebral Aneurysm Computer-Aided Detection System by combing MSER, SURF and SIFT descriptors

Abstract

Computer-Assisted Detection (CAD) systems for detecting Cerebral Aneurysms (CA) present an important influence in the prevention of Intracranial HSA (Subarachnoid Hemorrhage), their usefulness haves been reported. We propose in this paper, a CAD to detect CA in DSA angiographic images by combining different methods for robust features/interest points detector which are Maximally Stable Extremal Regions (MSER), Speed Up Robust Features (SURF) and Scale Invariant Feature Transform (SIFT). The results on the proposed CAD over the provided benchmark are very encouraging.