Meeting Banner
Abstract #3516

Task-aware 3D-Convolutional Neural Networks for Detailed Brain Parcellation

Junchuan Peng1, Yashi Nan1, Li Zhao2, Huanhui Xiao1, and Silun Wang1
1YIWEI Medical Technology Co., Ltd, Shenzhen, China, 2College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China

Morphological changes in neurodegenerative diseases can be detected with structural MR images, but it requires detailed brain parcellation. Therefore, a task-aware V-Net was proposed to segment the brain into 40 regions. Task-aware features were achieved by three cascading branches, including brain and non-brain regions, 25 regions with the bilateral regions grouped, and 40 regions, respectively. The proposed model was developed on 8938 subjects and validated using additional196 subjects. The proposed method outperformed the typical 3D U-Net and V-Net, and achieved state-of-the-art results on both datasets with a mean Dice score of 0.886 ± 0.029 and 0.874 ± 0.013, respectively.

This abstract and the presentation materials are available to members only; a login is required.

Join Here