477 citations · 700 across the 16 of their papers we have counts for
16 papers
Tell2Reg: Establishing spatial correspondence between images by the same language prompts
Wen Yan, Qianye Yang, Shiqi Huang +6
Spatial correspondence can be represented by pairs of segmented regions, such that the image registration networks aim to segment corresponding regions rather than predicting displ…
Biomechanics-informed Non-rigid Medical Image Registration and its Inverse Material Property Estimation with Linear and Nonlinear Elasticity
Zhe Min, Zachary M. C. Baum, Shaheer U. Saeed +4
This paper investigates both biomechanical-constrained non-rigid medical image registrations and accurate identifications of material properties for soft tissues, using physics-inf…
Weakly supervised localisation of prostate cancer using reinforcement learning for bi-parametric MR images
Martynas Pocius, Wen Yan, Dean C. Barratt +4
In this paper we propose a reinforcement learning based weakly supervised system for localisation. We train a controller function to localise regions of interest within an image by…
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,…
Combiner and HyperCombiner Networks: Rules to Combine Multimodality MR Images for Prostate Cancer Localisation
Wen Yan, Bernard Chiu, Ziyi Shen +8
One of the distinct characteristics in radiologists' reading of multiparametric prostate MR scans, using reporting systems such as PI-RADS v2.1, is to score individual types of MR…
A hybrid CNN-RNN approach for survival analysis in a Lung Cancer Screening study
Yaozhi Lu, Shahab Aslani, An Zhao +5
In this study, we present a hybrid CNN-RNN approach to investigate long-term survival of subjects in a lung cancer screening study. Subjects who died of cardiovascular and respirat…