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Abstract #2839

Infant brain extraction in T2 weighted MR images using k-means clustering and spatial information

Inyoung Bae1, JungHyun Song1, Seonyeong Shin1, Jun-Young Chung1, Sung-Ho Woo2, Dongchan Kim3, and Yeji Han1

1Gachon Advanced Institute for Health Science and Technology (GAIST), Gachon University, Incheon, Republic of Korea, 2Neuroscience Research Institute, Incheon, Republic of Korea, 3College of Health Science, Gachon University, Incheon, Republic of Korea

Brain extraction is an essential pre-processing step for brain image analysis. In this work, a new brain extraction technique for T2 weighted image of an infant brain with pathological characteristics is proposed to reduce the error of conventional techniques caused by variations in contrast and brain size of infant brain from that of the adult brain. We used k-means clustering, spatial information, and morphological approaches to improve brain extraction technique. Quantitative analysis was conducted using the dice ratio compared with the results of manual segmentation.

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