4 citations · 11 across the 11 of their papers we have counts for
11 papers
Preserving Cardiac Integrity: A Topology-Infused Approach to Whole Heart Segmentation
Chenyu Zhang, Wenxue Guan, Xiaodan Xing +1
Whole heart segmentation (WHS) supports cardiovascular disease (CVD) diagnosis, disease monitoring, treatment planning, and prognosis. Deep learning has become the most widely used…
The Beauty or the Beast: Which Aspect of Synthetic Medical Images Deserves Our Focus?
Xiaodan Xing, Yang Nan, Federico Felder +2
Training medical AI algorithms requires large volumes of accurately labeled datasets, which are difficult to obtain in the real world. Synthetic images generated from deep generati…
You Don't Have to Be Perfect to Be Amazing: Unveil the Utility of Synthetic Images
Xiaodan Xing, Federico Felder, Yang Nan +3
Synthetic images generated from deep generative models have the potential to address data scarcity and data privacy issues. The selection of synthesis models is mostly based on ima…
Less is More: Unsupervised Mask-guided Annotated CT Image Synthesis with Minimum Manual Segmentations
Xiaodan Xing, Giorgos Papanastasiou, Simon Walsh +1
As a pragmatic data augmentation tool, data synthesis has generally returned dividends in performance for deep learning based medical image analysis. However, generating correspond…
Hierarchical Perception Adversarial Learning Framework for Compressed Sensing MRI
Zhifan Gao, Yifeng Guo, Jiajing Zhang +2
The long acquisition time has limited the accessibility of magnetic resonance imaging (MRI) because it leads to patient discomfort and motion artifacts. Although several MRI techni…
Non-Imaging Medical Data Synthesis for Trustworthy AI: A Comprehensive Survey
Xiaodan Xing, Huanjun Wu, Lichao Wang +5
Data quality is the key factor for the development of trustworthy AI in healthcare. A large volume of curated datasets with controlled confounding factors can help improve the accu…
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…
Unsupervised Tissue Segmentation via Deep Constrained Gaussian Network
Yang Nan, Peng Tang, Guyue Zhang +5
Tissue segmentation is the mainstay of pathological examination, whereas the manual delineation is unduly burdensome. To assist this time-consuming and subjective manual step, rese…
Swin Deformable Attention U-Net Transformer (SDAUT) for Explainable Fast MRI
Jiahao Huang, Xiaodan Xing, Zhifan Gao +1
Fast MRI aims to reconstruct a high fidelity image from partially observed measurements. Exuberant development in fast MRI using deep learning has been witnessed recently. Meanwhil…
CS: A Controllable and Simultaneous Synthesizer of Images and Annotations with Minimal Human Intervention
Xiaodan Xing, Jiahao Huang, Yang Nan +5
The destitution of image data and corresponding expert annotations limit the training capacities of AI diagnostic models and potentially inhibit their performance. To address such…
Data Harmonisation for Information Fusion in Digital Healthcare: A State-of-the-Art Systematic Review, Meta-Analysis and Future Research Directions
Yang Nan, Javier Del Ser, Simon Walsh +23
Removing the bias and variance of multicentre data has always been a challenge in large scale digital healthcare studies, which requires the ability to integrate clinical features…