Choroid Plexus Segmentation Using Optimized 3D U-Net

The choroid plexus is the primary organ that secretes the cerebrospinal fluid. Its structure and function may be associated with the brain drainage pathway and the clearance of amyloid-beta in Alzheimer?s Disease. However, choroid plexus segmentation methods have rarely been studied. Therefore, the purpose of this work is to fill the gap using a deep convolutional network. MR images of 10 healthy subjects (75.5ñ8.0 years) were retrospectively selected from the Alzheimer's Disease Neuroimaging Initiative database (ADNI). The benchmark of choroid plexus segmentation was provided by the FreeSurfer package and manual correction. A 3D U-Net was developed and optimized in the patch extraction, augmentation, and loss function. In leave-one-out cross-validations, the optimized U-Net provided superior performance compared to the FreeSurfer results (Dice score 0.732ñ0.046 vs 0.581ñ0.093, Jaccard coefficient 0.579ñ0.057 vs 0.416ñ0.091, 95% Hausdorff distance 1.871ñ0.549 vs 7.257ñ5.038, and sensitivity 0.761ñ0.078 vs 0.539ñ0.117).