One-Foundation-Model-for-All

Structural magnetic resonance (MR) imaging is a vital tool for neuroimaging analyses, but the quality of MR images is often degraded by various factors, such as motion artifacts, large slice thickness, and imaging noise. These factors can cause confounding effects and pose significant challenges, especially in young children who tend to move during acquisition.

Method

This manuscript describes a flexible and easy-to-implement method for significantly improving the quality of brain MR images through motion removal, super resolution, and denoising.

File descriptions

Template

Template_T1_24.xxx: a template for histogram matching of T1w images (24 months).

Testing_subjects

The subjects in the folder Testing_subjects are only randomly selected examples for the model testing.

subject-x-T1.xxx: the T1w MRI.

Steps:

1. System requirements:

   Ubuntu 18.04.5

   Caffe version 1.0.0-rc3

   To make sure of consistency with our used version (e.g., including 3d convolution, and WeightedSoftmaxWithLoss, etc.), we strongly recommend installing Caffe using our released caffe_rc3. The installation steps are easy to perform without compilation procedure:

   a. Download caffe_rc3 and caffe_lib.

   caffe_rc3: https://github.com/YueSun814/caffe_rc3

   caffe_lib: https://github.com/YueSun814/caffe_lib

   b. Add paths of caffe_lib, and caffe_rc3/python to your ~/.bashrc file. For example, if the folders are saved in the home path, then add the following commands to the ~/.bashrc

   export LD_LIBRARY_PATH=~/caffe_lib:$LD_LIBRARY_PATH

   export PYTHONPATH=~/caffe_rc3/python:$PATH

   c. Test Caffe

   cd caffe_rc3/build/tools

   ./caffe

   Then, the screen will show:

   

   Typical install time: few minutes.

2. Testing steps: In folder: Pretrained_models