Vessel and intracranial aneurysm segmentation using multi-range filters and local variances.
Segmentation of vessels and brain aneurysms on non-invasive and flow-sensitive phase contrast magnetic resonance angiographic (PCMRA) images is essential in the detection of vascular diseases, in particular, intracranial aneurysms. In this paper, we devise a novel method based on multi-range filters and local variances to perform segmentation of vessels and intracranial aneurysms on PCMRA images. The proposed method is validated and compared using a synthetic and numerical image volume and four clinical cases. It is experimentally shown that the proposed method is capable of segmenting vessels and aneurysms with various sizes on PCMRA images.
Lo Kwee-Seong Medical Image Analysis Laboratory, Department of Computer Science and Engineering, The Hong Kong University of Science and Technology, Hong Kong maxlawwk@cse.ust.hk
Max W K
MW
Law
Albert C S
AC
Chung
D000465:Algorithms; D001185:Artificial Intelligence; D002536:Cerebral Arteries / Q000473:pathology*; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D002532:Intracranial Aneurysm / Q000175:diagnosis*; D018810:Magnetic Resonance Angiography / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted