| Paper Abstract and Keywords |
| Presentation |
2011-09-06 10:45
Brain Segmentation based on intensity distribution and brain shape in neonatal magnetic resonance image Aya Hashioka (Univ. of Hyogo), Kei Kuramoto (Univ. of Hyogo/ WPI-IFReC), Kosuke Yamaguchi (Univ. of Hyogo), Syoji Kobashi (Univ. of Hyogo/ WPI-IFReC), Yuki Wakata, Kumiko Ando, Reiichi Ishikura (Hyogo College of Medicine), Tomomoto Ishikawa (Ishikawa Hospital), Shozo Hirota (Hyogo College of Medicine), Yutaka Hata (Univ. of Hyogo/ WPI-IFReC) MI2011-51 |
| Abstract |
(in Japanese) |
(See Japanese page) |
| (in English) |
For diagnosis of the neonatal cerebral disorders, it is useful to measure cerebral volume and surface area using magnetic resonance (MR) image. To measure cerebral volume and surface area, a brain segmentation method is required. However, there are few studies on automated neonatal brain segmentation. This study proposes an automated brain segmentation method for neonatal brain. The proposed method segments the cerebral region by using fuzzy deformable model. Then, the segmented area is evaluated with respect to the shape of whole head, and segmentation parameters of fuzzy deformable model are updated. Segmentation, evaluation and parameter update processes are iterated until satisfying predefined condition. The initial parameters are selected using Bayesian classification.Experimental results in 34 neonatal subjects (revised age between -2weeks and 1day and 2 years 5 months) showed that the brain region was segmented with sensitivity 99.4% and false-positive rate of 29.6%. |
| Keyword |
(in Japanese) |
(See Japanese page) |
| (in English) |
MR image / cerebral surface / skull stripping / brain segmentation / Bayesian classification / neonate / / |
| Reference Info. |
IEICE Tech. Rep., vol. 111, no. 199, MI2011-51, pp. 21-26, Sept. 2011. |
| Paper # |
MI2011-51 |
| Date of Issue |
2011-08-30 (MI) |
| ISSN |
Print edition: ISSN 0913-5685 Online edition: ISSN 2432-6380 |
Copyright and reproduction |
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| Download PDF |
MI2011-51 |