TY  - EJOU
AU  - Xiao, Xinyi 
AU  - Pan, Dongbo 
AU  - Yuan, Jianjun 

TI  - SC-Net: A New U-Net Network for Hippocampus Segmentation
T2  - Intelligent Automation \& Soft Computing

PY  - 2023
VL  - 37
IS  - 3
SN  - 2326-005X

AB  - Neurological disorders like Alzheimer’s disease have a significant impact on the lives and health of the elderly as the aging population continues to grow. Doctors can achieve effective prevention and treatment of Alzheimer’s disease according to the morphological volume of hippocampus. General segmentation techniques frequently fail to produce satisfactory results due to hippocampus’s small size, complex structure, and fuzzy edges. We develop a new SC-Net model using complete brain MRI images to achieve high-precision segmentation of hippocampal structures. The proposed network improves the accuracy of hippocampal structural segmentation by retaining the original location information of the hippocampus. Extensive experimental results demonstrate that the proposed SC-Net model is significantly better than other models, and reaches a Dice similarity coefficient of 0.885 on Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset.
KW  - SC-Net; hippocampus; brain MRI images; image segmentation

DO  - 10.32604/iasc.2023.041208