CAST: A multi-scale convolutional neural network based automated hippocampal subfield segmentation toolbox.

ABSTRACT: In this study, we developed a multi-scale Convolutional neural network based Automated hippocampal subfield Segmentation Toolbox (CAST) for automated segmentation of hippocampal subfields. Although training CAST required approximately three days on a single workstation with a high-quality GPU card, CAST can segment a new subject in less than 1 ​min even with GPU acceleration disabled, thus this method is more time efficient than current automated methods and manual segmentation. This toolbox is highly flexible with either a single modality or multiple modalities and can be easily set up to be trained with a researcher's unique data. A 3D multi-scale deep convolutional neural network is the key algorithm used in the toolbox. The main merit of multi-scale images is the capability to capture

SUBMITTER: Yang Z 

PROVIDER: S-EPMC7442241 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature