An effective approach for white matter, grey matter, and cerebrospinal fluid segmentation from 3D brain MRI
by Pham The Bao; Tuan Tran; Tran Anh Tuan; Le Nhi Lam Thuy; Jin Young Kim
International Journal of Intelligent Information and Database Systems (IJIIDS), Vol. 14, No. 4, 2021

Abstract: According to the World Alzheimer Report 2019, over 50 million people are living with dementia globally and it will increase to 152 million by 2050. Alzheimer's disease (AD) is a common type of dementia. One of the methods for Alzheimer's disease detection is using medical imaging especially using magnetic resonance imaging (MRI) in the brain concerning the white matter (WM), grey matter (GM), and cerebrospinal fluid regions (CSF). There are many methods based on a 3D CNN model for tissue segmentation but the disadvantage of the 3D model compared with the 2D model is the number of training objects will be decreased and the computation cost is increased. In this research, we proposed an effective approach to segment automatically WM, GM, and CSF in 3D brain MRI by using 2D and 3D CNN model combination. Our proposed method was evaluated with IBSR 18 and compared against state-of-the-art methods. The accuracy is 0.93, 0.92 and 0.79 for WM, GM, and CSF segmentation.

Online publication date: Thu, 28-Oct-2021

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