Title :
Automated finding of the Willis ring in MR angiography images using fuzzy knowledge base
Author :
Kobashi, Syoji ; Kondo, Katsuya ; Hata, Yutaka
Author_Institution :
Comput. Eng. Div., Himeji Inst. of Technol., Japan
Abstract :
This paper proposes an automated method for finding the Willis ring from the human brain MR angiography (MRA) images, which can depict cerebral arteries with high contrast. It strongly helps screening of unruptured cerebral aneurysm in MRA images. The proposed method consists of (1) segmenting cerebral arteries from MRA images, (2) skeletonization of artery trees, and detection of furcations, and (3) finding furcations in the Willis ring using genetic algorithm (GA) based on fuzzy knowledge base (fuzzy KB). Fuzzy KB gives knowledge about the Willis ring that consists of arteries and furcations. GA finds a set of furcations by optimizing an objective function. The objective function used by GA estimates fitness of a set of furcations using fuzzy KB. Our method was first applied to a 3-D phantom data generated by computer simulation. The result demonstrated that our method detected all suitable furcations correctly. Next, it was applied to MRA volume data of two normal healthy volunteers. In any cases, the proposed method detected desired all furcations in the Willis ring.
Keywords :
biomedical MRI; fuzzy logic; genetic algorithms; image segmentation; image thinning; medical image processing; 3-D phantom data; GA; MRA image; Willis Ring automated finding; artery tree skeletonization; cerebral artery segmentation; computer simulation; furcation detection; fuzzy KB; fuzzy knowledge base; genetic algorithm; human brain MR angiography; objective function; Aneurysm; Angiography; Arteries; Biomedical imaging; Computed tomography; Genetic algorithms; Humans; Image segmentation; Medical diagnostic imaging; X-ray imaging;
Conference_Titel :
Multiple-Valued Logic, 2003. Proceedings. 33rd International Symposium on
Print_ISBN :
0-7695-1918-0
DOI :
10.1109/ISMVL.2003.1201389