Xinyu Ye1, Yuan Lian1, Pylypenko Dmytro1, Yajing Zhang2, and Hua Guo1
1Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China, 2MR Clinical Science, Philips Healthcare, Suzhou, China
1Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China, 2MR Clinical Science, Philips Healthcare, Suzhou, China
We demonstrate that the deep learning-based
method can jointly increase resolution and correct distortions for SSh-EPI DWI.
Based on the results, our method provides more consistent DWI images with the
undistorted high-resolution reference images.
Fig.
3. Comparison between state-of-the-art methods
with the proposed method using the test subject. 2 representative slices of b0 and mean DWI images are
selected. The red arrowheads point at regions where residual distortion and blurring artifacts still exist after distortion correction.
Fig. 2. Validation results of the proposed
method. Input LR SSh-EPI, T2w-TSE, reference PSF-EPI and
the reconstructed results are shown in the figure. b0 and mean DWI results show
consistency with the reference image.
