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Proceedings Paper

Performance evaluation of an automatic segmentation method of cerebral arteries in MRA images by use of a large image database
Author(s): Yoshikazu Uchiyama; Tatsunori Asano; Takeshi Hara; Hiroshi Fujita; Yasutomi Kinosada; Takahiko Asano; Hiroki Kato; Masayuki Kanematsu; Hiroaki Hoshi; Toru Iwama
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Paper Abstract

The detection of cerebrovascular diseases such as unruptured aneurysm, stenosis, and occlusion is a major application of magnetic resonance angiography (MRA). However, their accurate detection is often difficult for radiologists. Therefore, several computer-aided diagnosis (CAD) schemes have been developed in order to assist radiologists with image interpretation. The purpose of this study was to develop a computerized method for segmenting cerebral arteries, which is an essential component of CAD schemes. For the segmentation of vessel regions, we first used a gray level transformation to calibrate voxel values. To adjust for variations in the positioning of patients, registration was subsequently employed to maximize the overlapping of the vessel regions in the target image and reference image. The vessel regions were then segmented from the background using gray-level thresholding and region growing techniques. Finally, rule-based schemes with features such as size, shape, and anatomical location were employed to distinguish between vessel regions and false positives. Our method was applied to 854 clinical cases obtained from two different hospitals. The segmentation of cerebral arteries in 97.1%(829/854) of the MRA studies was attained as an acceptable result. Therefore, our computerized method would be useful in CAD schemes for the detection of cerebrovascular diseases in MRA images.

Paper Details

Date Published: 3 March 2009
PDF: 7 pages
Proc. SPIE 7260, Medical Imaging 2009: Computer-Aided Diagnosis, 72602J (3 March 2009); doi: 10.1117/12.811435
Show Author Affiliations
Yoshikazu Uchiyama, Graduate School of Medicine, Gifu Univ. (Japan)
Tatsunori Asano, Graduate School of Medicine, Gifu Univ. (Japan)
Takeshi Hara, Graduate School of Medicine, Gifu Univ. (Japan)
Hiroshi Fujita, Graduate School of Medicine, Gifu Univ. (Japan)
Yasutomi Kinosada, Graduate School of Medicine, Gifu Univ. (Japan)
Takahiko Asano, Graduate School of Medicine, Gifu Univ. (Japan)
Hiroki Kato, Graduate School of Medicine, Gifu Univ. (Japan)
Masayuki Kanematsu, Graduate School of Medicine, Gifu Univ. (Japan)
Hiroaki Hoshi, Graduate School of Medicine, Gifu Univ. (Japan)
Toru Iwama, Graduate School of Medicine, Gifu Univ. (Japan)


Published in SPIE Proceedings Vol. 7260:
Medical Imaging 2009: Computer-Aided Diagnosis
Nico Karssemeijer; Maryellen L. Giger, Editor(s)

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