Fuzzy-based segmentation of brain parenchymal regions with Alzheimer's disease into cerebral cortex and white matter in 3.0-T magnetic resonance images

Chiaki Tokunaga, Hidetaka Arimura, Takashi Yoshiura, Yasuo Yamashita, Taiki Magome, Hiroshi Honda, Hideki Hirata, Fukai Toyofuku, Masafumi Ohki

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

It would be very important to estimate the degree of cerebral atrophy based on cortical regions for diagnosis of Alzheimer's disease (AD). However, it would be still challenging to segment brain parenchymal regions with AD into cerebral cortex and white matter when the boundary between them is unclear due to the presence of AD showing in magnetic resonance (MR) images. Our purpose of this study was to develop an automated segmentation of the brain parenchyma into cerebral cortical and white matter regions with AD in three-dimensional (3D) T1-weighted MR images. Our proposed method consisted of extraction of a brain parenchymal region based on a brain model matching and segmentation of the brain parenchyma into cerebral cortical and white matter regions based on a fuzzy c-means (FCM) algorithm. We applied the proposed method to MR images of the whole brain obtained from 9 cases, including 4 AD cases and 5 control cases. The mean volume percentages of the brain parenchymal region in the respective AD patients and controls were 41.7% and 45.2% for cortical cortex region, 58.3% and 54.8% for white matter region, respectively.

Original languageEnglish
Title of host publication2010 World Automation Congress, WAC 2010
Publication statusPublished - Dec 1 2010
Event2010 World Automation Congress, WAC 2010 - Kobe, Japan
Duration: Sep 19 2010Sep 23 2010

Publication series

Name2010 World Automation Congress, WAC 2010

Other

Other2010 World Automation Congress, WAC 2010
CountryJapan
CityKobe
Period9/19/109/23/10

Fingerprint

Magnetic resonance
Brain
Brain models

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering

Cite this

Tokunaga, C., Arimura, H., Yoshiura, T., Yamashita, Y., Magome, T., Honda, H., ... Ohki, M. (2010). Fuzzy-based segmentation of brain parenchymal regions with Alzheimer's disease into cerebral cortex and white matter in 3.0-T magnetic resonance images. In 2010 World Automation Congress, WAC 2010 [5665596] (2010 World Automation Congress, WAC 2010).

Fuzzy-based segmentation of brain parenchymal regions with Alzheimer's disease into cerebral cortex and white matter in 3.0-T magnetic resonance images. / Tokunaga, Chiaki; Arimura, Hidetaka; Yoshiura, Takashi; Yamashita, Yasuo; Magome, Taiki; Honda, Hiroshi; Hirata, Hideki; Toyofuku, Fukai; Ohki, Masafumi.

2010 World Automation Congress, WAC 2010. 2010. 5665596 (2010 World Automation Congress, WAC 2010).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Tokunaga, C, Arimura, H, Yoshiura, T, Yamashita, Y, Magome, T, Honda, H, Hirata, H, Toyofuku, F & Ohki, M 2010, Fuzzy-based segmentation of brain parenchymal regions with Alzheimer's disease into cerebral cortex and white matter in 3.0-T magnetic resonance images. in 2010 World Automation Congress, WAC 2010., 5665596, 2010 World Automation Congress, WAC 2010, 2010 World Automation Congress, WAC 2010, Kobe, Japan, 9/19/10.
Tokunaga C, Arimura H, Yoshiura T, Yamashita Y, Magome T, Honda H et al. Fuzzy-based segmentation of brain parenchymal regions with Alzheimer's disease into cerebral cortex and white matter in 3.0-T magnetic resonance images. In 2010 World Automation Congress, WAC 2010. 2010. 5665596. (2010 World Automation Congress, WAC 2010).
Tokunaga, Chiaki ; Arimura, Hidetaka ; Yoshiura, Takashi ; Yamashita, Yasuo ; Magome, Taiki ; Honda, Hiroshi ; Hirata, Hideki ; Toyofuku, Fukai ; Ohki, Masafumi. / Fuzzy-based segmentation of brain parenchymal regions with Alzheimer's disease into cerebral cortex and white matter in 3.0-T magnetic resonance images. 2010 World Automation Congress, WAC 2010. 2010. (2010 World Automation Congress, WAC 2010).
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