5 papers
Interpretable Probabilistic Medical Image Segmentation via Gaussian Process with Explicit Modelling of Annotation Bias and Variability
Qi Li, Yuliang Huang, Shaheer U. Saeed +7
Deep learning-based medical image segmentation models are trained using annotations that exhibit systematic bias and variability across raters. While probabilistic multi-rater appr…
Deep EM with Hierarchical Latent Label Modelling for Multi-Site Prostate Lesion Segmentation
Wen Yan, Yipei Wang, Shiqi Huang +5
Label variability is a major challenge for prostate lesion segmentation. In multi-site datasets, annotations often reflect centre-specific contouring protocols, causing segmentatio…
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…
Multimodal Conditional MeshGAN for Personalized Aneurysm Growth Prediction
Long Chen, Ashiv Patel, Mengyun Qiao +8
Personalized, accurate prediction of aortic aneurysm progression is essential for timely intervention but remains challenging due to the need to model both subtle local deformation…
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…