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

4 citations · 10 across the 5 of their papers we have counts for

collaborators

5 papers

eess.IV2023

Dynamic Multimodal Information Bottleneck for Multimodality Classification

Yingying Fang, Shuang Wu, Sheng Zhang +5

Effectively leveraging multimodal data such as various images, laboratory tests and clinical information is gaining traction in a variety of AI-based medical diagnosis and prognosi…

eess.IV2022★ 4 cited

Fuzzy Attention Neural Network to Tackle Discontinuity in Airway Segmentation

Yang Nan, Javier Del Ser, Zeyu Tang +7

Airway segmentation is crucial for the examination, diagnosis, and prognosis of lung diseases, while its manual delineation is unduly burdensome. To alleviate this time-consuming a…

eess.IV2022★ 4 cited

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

Jiahao Huang, Yingying Fang, Yang Nan +9

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,…

eess.IV2022

Explainable COVID-19 Infections Identification and Delineation Using Calibrated Pseudo Labels

Ming Li, Yingying Fang, Zeyu Tang +5

The upheaval brought by the arrival of the COVID-19 pandemic has continued to bring fresh challenges over the past two years. During this COVID-19 pandemic, there has been a need f…

eess.IV2022★ 2 cited

Swin Transformer for Fast MRI

Jiahao Huang, Yingying Fang, Yinzhe Wu +6

Magnetic resonance imaging (MRI) is an important non-invasive clinical tool that can produce high-resolution and reproducible images. However, a long scanning time is required for…