1 citations · 3 across the 8 of their papers we have counts for
8 papers
Causal-Adversarial Probing of Clinical Covariates for Prostate MRI Grading
Yipei Wang, Shiqi Huang, Wen Yan +6
Deep learning models for prostate MRI-based cancer grading may encode clinical covariates that either reflect useful disease-related signal or non-generalising shortcut information…
Maximizing T2-Only Prostate Cancer Localization from Expected Diffusion Weighted Imaging
Weixi Yi, Yipei Wang, Wen Yan +10
Multiparametric MRI is increasingly recommended as a first-line noninvasive approach to detect and localize prostate cancer, requiring at minimum diffusion-weighted (DWI) and T2-we…
ProFound: A moderate-sized vision foundation model for multi-task prostate imaging
Yipei Wang, Yinsong Xu, Weixi Yi +11
Many diagnostic and therapeutic clinical tasks for prostate cancer increasingly rely on multi-parametric MRI. Automating these tasks is challenging because they necessitate expert…
Depth Augmented and FE Free 3D/2D Liver Registration for Laparoscopic Liver AR
Hanyuan Zhang, Lucas He, Runlong He +6
Augmented reality (AR) guidance in laparoscopic liver surgery requires accurate registration of preoperative 3D models to intraoperative 2D video, but remains challenging due to pa…
Analysis of Image-and-Text Uncertainty Propagation in Multimodal Large Language Models with Cardiac MR-Based Applications
Yucheng Tang, Yunguan Fu, Weixi Yi +4
Multimodal large language models (MLLMs) can process and integrate information from multimodality sources, such as text and images. However, interrelationship among input modalitie…
A versatile foundation model for cine cardiac magnetic resonance image analysis tasks
Yunguan Fu, Wenjia Bai, Weixi Yi +7
Here we present a versatile foundation model that can perform a range of clinically-relevant image analysis tasks, including segmentation, landmark localisation, diagnosis, and pro…
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…
Boundary-RL: Reinforcement Learning for Weakly-Supervised Prostate Segmentation in TRUS Images
Weixi Yi, Vasilis Stavrinides, Zachary M. C. Baum +5
We propose Boundary-RL, a novel weakly supervised segmentation method that utilises only patch-level labels for training. We envision the segmentation as a boundary detection probl…