Non-Imaging Medical Data Synthesis for Trustworthy AI: A Comprehensive Survey

no code implementations • 17 Sep 2022 • Xiaodan Xing, Huanjun Wu, Lichao Wang, Iain Stenson, May Yong, Javier Del Ser, Simon Walsh, Guang Yang

Data quality is the key factor for the development of trustworthy AI in healthcare.

Data and Physics Driven Learning Models for Fast MRI -- Fundamentals and Methodologies from CNN, GAN to Attention and Transformers

no code implementations • 1 Apr 2022 • Jiahao Huang, Yingying Fang, Yang Nan, Huanjun Wu, Yinzhe Wu, Zhifan Gao, Yang Li, Zidong Wang, Pietro Lio, Daniel Rueckert, Yonina C. Eldar, Guang Yang

Research studies have shown no qualms about using data driven deep learning models for downstream tasks in medical image analysis, e. g., anatomy segmentation and lesion detection, disease diagnosis and prognosis, and treatment planning.

Anatomy Explainable Models +3

Fast MRI Reconstruction: How Powerful Transformers Are?

1 code implementation • 23 Jan 2022 • Jiahao Huang, Yinzhe Wu, Huanjun Wu, Guang Yang

In particular, a generative adversarial network (GAN) based Swin transformer (ST-GAN) was introduced for the fast MRI reconstruction.

Generative Adversarial Network MRI Reconstruction

Swin Transformer for Fast MRI

2 code implementations • 10 Jan 2022 • Jiahao Huang, Yingying Fang, Yinzhe Wu, Huanjun Wu, Zhifan Gao, Yang Li, Javier Del Ser, Jun Xia, Guang Yang

The IM and OM were 2D convolutional layers and the FEM was composed of a cascaded of residual Swin transformer blocks (RSTBs) and 2D convolutional layers.

MRI Reconstruction