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首页> 外文会议>World Automation Congress >Fuzzy-based segmentation of brain parenchymal regions with alzheimer's disease into cerebral cortex and white matter in 3.0-T magnetic resonance images
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Fuzzy-based segmentation of brain parenchymal regions with alzheimer's disease into cerebral cortex and white matter in 3.0-T magnetic resonance images

机译：3.0-T磁共振图像中阿尔茨海默病的脑实质区脑实质区的模糊分割

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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.
机译：估计基于皮质区域的脑萎缩程度是非常重要的，用于诊断阿尔茨海默病（AD）。然而，当由于在磁共振（MR）图像中显示的广告存在时，在它们之间的边界不明确时，将脑实质区域分段为脑皮层和白质仍然挑战。我们本研究的目的是在三维（3D）T1加权的MR图像中，在三维（3D）T1加权MR图像中，将脑检医的自动分割成脑皮质和白质。我们所提出的方法包括基于模糊C型算法（FCM）算法的脑模型匹配和脑诊所的脑模型匹配和细分脑考科和白质区分割组成。我们将提出的方法应用于9例中的全脑MR图像，包括4个AD病例和5例控制病例。各种AD患者和对照中脑实质区域的平均体积百分比为皮质皮质区域的41.7％和45.2％，分别为白质区的58.3％和54.8％。

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