Automatic segmentation of hippocampal region in brain MRI images
XU Jingjing
HUANG Dian
WU Xue
HU Min
LYU Hao
HAN Shipeng
Abstract：Objective To achieve automatic and accurate segmentation of hippocampal region in brain MRI images.Methods AF-VNet,an automatic hippocampus segmentation framework based on deep learning,was proposed to improve the accuracy of hippocampus segmentation by adding attention mechanism module to the output layer of the network.In addition,the Focal Loss function was introduced and the number of channels was increased to avoid unbalanced training samples.Results The Dice score obtained by AF-VNet was 0.878 7±0.028 1,which was 2.37％higher than the benchmark VNet.Conclusion This method improves the accuracy of hippocampus segmentation,has certain clinical application value,and can provide an auxiliary tool for the diagnosis and treatment of neurodegenerative diseases.
Keywords：hippocampus segmentationdeep learningattention mechanismloss function
Publication Date：2024-11-28
Online Publishing Date：2026-08-26(First online date of this platform, not the publication date of the document)
Pages：6( 1227-1232 )