Learning ADC maps from accelerated radial k-space diffusion-weighted MRI in mice using a deep CNN-transformer model.

ABSTRACT:

Purpose

To accelerate radially sampled diffusion weighted spin-echo (Rad-DW-SE) acquisition method for generating high quality ADC maps.

Methods

A deep learning method was developed to generate accurate ADC maps from accelerated DWI data acquired with the Rad-DW-SE method. The deep learning method integrates convolutional neural networks (CNNs) with vision transformers to generate high quality ADC maps from accelerated DWI data, regularized by a monoexponential ADC model fitting term. A model was trained on DWI data of 147 mice and evaluated on DWI data of 36 mice, with acceleration factors of 4× and 8× compared to the original acquisition parameters.

Results

Ablation studies and experimental results have demonstrated that the proposed deep learning model generates hi

SUBMITTER: Li Y 

PROVIDER: S-EPMC10691280 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature