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20222024
most citedFuzzy Attention Neural Network to Tackle Discontinuity in Airway Segmentation

4 citations · 11 across the 11 of their papers we have counts for

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6 papers · 1 filter

cs.LG2022★ 3 cited

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…

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

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…

cs.CV2022

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…

eess.IV2022

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…

cs.AI2022

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…