output
20172024
most citedA Transformer-based Generative Adversarial Network for Brain Tumor Segmentation

45 citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

collaborating institutions

4 papers

eess.SP2024★ 13 cited

Data and Physics driven Deep Learning Models for Fast MRI Reconstruction: Fundamentals and Methodologies

Jiahao Huang, Yinzhe Wu, Fanwen Wang +17

Magnetic Resonance Imaging (MRI) is a pivotal clinical diagnostic tool, yet its extended scanning times often compromise patient comfort and image quality, especially in volumetric…

eess.IV2022★ 45 cited

A Transformer-based Generative Adversarial Network for Brain Tumor Segmentation

Liqun Huang, Long Chen, Baihai Zhang +1

Brain tumor segmentation remains a challenge in medical image segmentation tasks. With the application of transformer in various computer vision tasks, transformer blocks show the…

q-bio.QM2019★ 8 cited

Outcome-Driven Clustering of Acute Coronary Syndrome Patients using Multi-Task Neural Network with Attention

Eryu Xia, Xin Du, Jing Mei +8

Cluster analysis aims at separating patients into phenotypically heterogenous groups and defining therapeutically homogeneous patient subclasses. It is an important approach in dat…

cs.CV2017

Direct detection of pixel-level myocardial infarction areas via a deep-learning algorithm

Chenchu Xu, Lei Xu, Zhifan Gao +7

Accurate detection of the myocardial infarction (MI) area is crucial for early diagnosis planning and follow-up management. In this study, we propose an end-to-end deep-learning al…