Background: These days, many attempts have been done to specify the size and location
of aneurysms, leading to more successful surgical operation and less bleeding risk. In this paper,
a novel method is proposed to extract brain aneurysms from two dimensional x-ray angiography
Methods: The most acute challenges in detecting brain aneurysm are the complexity of vessel
structures and shape similarity between the aneurysm and vessel overlaps and vessel cross sections.
Therefore, researchers regarded removing vessel structures as an initial and crucial step to
detect aneurysm. Since the circularity feature is the most distinctive criteria for physicians to detect
aneurysm, firstly, we proposed a robust method based on Fast Circlet Transform (FCT) to localize
the aneurysm without needing to remove vessel structures. Then, to segment the detected aneurysm
more accurately, a modified Level Set algorithm is proposed. Finally, our proposed method
is quantitatively evaluated on two different datasets with different views, shapes, sizes, locations
Results & Conclusion: Experimental results show that the proposed system is reliable without
dealing with vessel structure removal challenges, reluctant false positive candidates, hard parameter
tuning and poor edge gradient.