51 citations · 178 across the 33 of their papers we have counts for
7 papers · 1 filter
Prototypical few-shot segmentation for cross-institution male pelvic structures with spatial registration
Yiwen Li, Yunguan Fu, Iani Gayo +12
The prowess that makes few-shot learning desirable in medical image analysis is the efficient use of the support image data, which are labelled to classify or segment new classes,…
Cross-Modality Image Registration using a Training-Time Privileged Third Modality
Qianye Yang, David Atkinson, Yunguan Fu +7
In this work, we consider the task of pairwise cross-modality image registration, which may benefit from exploiting additional images available only at training time from an additi…
Collaborative Quantization Embeddings for Intra-Subject Prostate MR Image Registration
Ziyi Shen, Qianye Yang, Yuming Shen +9
Image registration is useful for quantifying morphological changes in longitudinal MR images from prostate cancer patients. This paper describes a development in improving the lear…
The impact of using voxel-level segmentation metrics on evaluating multifocal prostate cancer localisation
Wen Yan, Qianye Yang, Tom Syer +6
Dice similarity coefficient (DSC) and Hausdorff distance (HD) are widely used for evaluating medical image segmentation. They have also been criticised, when reported alone, for th…
Image quality assessment for machine learning tasks using meta-reinforcement learning
Shaheer U. Saeed, Yunguan Fu, Vasilis Stavrinides +8
In this paper, we consider image quality assessment (IQA) as a measure of how images are amenable with respect to a given downstream task, or task amenability. When the task is per…
Image quality assessment by overlapping task-specific and task-agnostic measures: application to prostate multiparametric MR images for cancer segmentation
Shaheer U. Saeed, Wen Yan, Yunguan Fu +9
Image quality assessment (IQA) in medical imaging can be used to ensure that downstream clinical tasks can be reliably performed. Quantifying the impact of an image on the specific…
Few-shot image segmentation for cross-institution male pelvic organs using registration-assisted prototypical learning
Yiwen Li, Yunguan Fu, Qianye Yang +6
The ability to adapt medical image segmentation networks for a novel class such as an unseen anatomical or pathological structure, when only a few labelled examples of this class a…