System of generating data from diffusion-weighted images for pre-processing and method thereof

The system of generating data from diffusion-weighted images for pre-processing, implemented by at least one device, wherein the system comprises:

• a memory module, configured to store at least one computer readable instruction;
• and
• a processing module, connected to the storage module, configured to execute the at least one computer readable instruction to generate following modules:
• a parameter acquisition module, configured to acquire a processing parameter set, wherein the processing parameter set comprises diffusion information and defines a fiber tracking count and a predetermined brain template;
• an image acquisition module, configured to acquire a raw diffusion-weighted image and a raw T1-weighted image, wherein the raw diffusion-weighted image comprises data images and an image information;
• a data setting module, configured to set image processing data of the raw diffusion-weighted image based on the image information;
• a deviation processing module, configured to remove ring artifact of the raw diffusion-weighted image based on the diffusion information and the image processing data, perform a signal drift correction on the raw diffusion-weighted image based on the diffusion information and a plurality of B0 images comprised in the data images, and remove ring artifact of the raw T1-weighted image to generate a result T1-weighted image;
• a deformation processing module, configured to correct eddy current artifacts and head motion of the raw diffusion-weighted image processed by the deviation processing module, based on the b-value threshold and the image processing data
• a signal processing module, configured to remove a skull in a result T1-weighted image and divide tissues in the result T1-weighted image to generate a final T1 weighted processed image, and align the final T1 weighted processed image to the raw diffusion-weighted image to generate a T1-weighted image binary mask;
• a fiber tracking module, configured to use a fiber orientation distribution function to perform calculation on the T1-weighted image binary mask and the result diffusion-weighted image to generate a fiber tracking structure information based on the diffusion information and the fiber tracking count;
• and
• a map creating module, configured to align the result T1 weighted processed image to the predetermined brain template to generate a target brain template, and create a weighted brain-connectivity network based on the target brain template and the fiber tracking structure information.