Style Transfer and Self-Supervised Learning Powered Myocardium Infarction Super-Resolution Segmentation

no code implementations • 27 Sep 2023 • Lichao Wang, Jiahao Huang, Xiaodan Xing, Yinzhe Wu, Ramyah Rajakulasingam, Andrew D. Scott, Pedro F Ferreira, Ranil De Silva, Sonia Nielles-Vallespin, Guang Yang

This study proposes a pipeline that incorporates a novel style transfer model and a simultaneous super-resolution and segmentation model.

Segmentation Self-Supervised Learning +2

Deep Learning-based Diffusion Tensor Cardiac Magnetic Resonance Reconstruction: A Comparison Study

no code implementations • 31 Mar 2023 • Jiahao Huang, Pedro F. Ferreira, Lichao Wang, Yinzhe Wu, Angelica I. Aviles-Rivero, Carola-Bibiane Schonlieb, Andrew D. Scott, Zohya Khalique, Maria Dwornik, Ramyah Rajakulasingam, Ranil De Silva, Dudley J. Pennell, Sonia Nielles-Vallespin, Guang Yang

Our results indicate that the models we discussed in this study can be applied for clinical use at an acceleration factor (AF) of $\times 2$ and $\times 4$, with the D5C5 model showing superior fidelity for reconstruction and the SwinMR model providing higher perceptual scores.

MRI Reconstruction