2 citations · 4 across the 20 of their papers we have counts for
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On the Degrees of Freedom of Gridded Control Points in Learning-Based Medical Image Registration
Wen Yan, Qianye Yang, Yipei Wang +5
Many registration problems are ill-posed in homogeneous or noisy regions, and dense voxel-wise decoders can be unnecessarily high-dimensional. A sparse control-point parameterisati…
Promptable cancer segmentation using minimal expert-curated data
Lynn Karam, Yipei Wang, Veeru Kasivisvanathan +3
Automated segmentation of cancer on medical images can aid targeted diagnostic and therapeutic procedures. However, its adoption is limited by the high cost of expert annotations r…
T2-Only Prostate Cancer Prediction by Meta-Learning from Bi-Parametric MR Imaging
Weixi Yi, Yipei Wang, Natasha Thorley +6
Current imaging-based prostate cancer diagnosis requires both MR T2-weighted (T2w) and diffusion-weighted imaging (DWI) sequences, with additional sequences for potentially greater…
AI-assisted prostate cancer detection and localisation on biparametric MR by classifying radiologist-positives
Xiangcen Wu, Yipei Wang, Qianye Yang +5
Prostate cancer diagnosis through MR imaging have currently relied on radiologists' interpretation, whilst modern AI-based methods have been developed to detect clinically signific…
Poisson Ordinal Network for Gleason Group Estimation Using Bi-Parametric MRI
Yinsong Xu, Yipei Wang, Ziyi Shen +7
The Gleason groups serve as the primary histological grading system for prostate cancer, providing crucial insights into the cancer's potential for growth and metastasis. In clinic…
Semi-weakly-supervised neural network training for medical image registration
Yiwen Li, Yunguan Fu, Iani J. M. B. Gayo +11
For training registration networks, weak supervision from segmented corresponding regions-of-interest (ROIs) have been proven effective for (a) supplementing unsupervised methods,…