26 citations · 43 across the 23 of their papers we have counts for
8 papers · 1 filter
Hunting imaging biomarkers in pulmonary fibrosis: Benchmarks of the AIIB23 challenge
Yang Nan, Xiaodan Xing, Shiyi Wang +38
Airway-related quantitative imaging biomarkers are crucial for examination, diagnosis, and prognosis in pulmonary diseases. However, the manual delineation of airway trees remains…
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…
Post-COVID Highlights: Challenges and Solutions of AI Techniques for Swift Identification of COVID-19
Yingying Fang, Xiaodan Xing, Shiyi Wang +2
Since the onset of the COVID-19 pandemic in 2019, there has been a concerted effort to develop cost-effective, non-invasive, and rapid AI-based tools. These tools were intended to…
Style Transfer and Self-Supervised Learning Powered Myocardium Infarction Super-Resolution Segmentation
Lichao Wang, Jiahao Huang, Xiaodan Xing +7
This study proposes a pipeline that incorporates a novel style transfer model and a simultaneous super-resolution and segmentation model. The proposed pipeline aims to enhance diff…
SegmentAnything helps microscopy images based automatic and quantitative organoid detection and analysis
Xiaodan Xing, Chunling Tang, Yunzhe Guo +2
Organoids are self-organized 3D cell clusters that closely mimic the architecture and function of in vivo tissues and organs. Quantification of organoid morphology helps in studyin…
Real-Time Non-Invasive Imaging and Detection of Spreading Depolarizations through EEG: An Ultra-Light Explainable Deep Learning Approach
Yinzhe Wu, Sharon Jewell, Xiaodan Xing +4
A core aim of neurocritical care is to prevent secondary brain injury. Spreading depolarizations (SDs) have been identified as an important independent cause of secondary brain inj…
Enhancing Super-Resolution Networks through Realistic Thick-Slice CT Simulation
Zeyu Tang, Xiaodan Xing, Guang Yang
Deep learning-based Generative Models have the potential to convert low-resolution CT images into high-resolution counterparts without long acquisition times and increased radiatio…
Swin Deformable Attention Hybrid U-Net for Medical Image Segmentation
Lichao Wang, Jiahao Huang, Xiaodan Xing +1
Medical image segmentation is a crucial task in the field of medical image analysis. Harmonizing the convolution and multi-head self-attention mechanism is a recent research focus…