Improving performance robustness of subject-based brain segmentation software.

Jong-Hyeok ParkKyung-Il ParkDongmin KimMyungjae LeeShinuk KangSeung Joo KangDae Hyun Yoonnull null

Published in: Encephalitis (Seoul, Korea) (2023)

Data augmentation and preindicator-based preprocessing of training data can improve the performance of AI-based brain segmentation software, both increasing the generalizability and stability of brain segmentation software.

Keyphrases

deep learning
resting state
convolutional neural network
white matter
data analysis
functional connectivity
electronic health record
artificial intelligence
big data
multiple sclerosis
machine learning
virtual reality