Given that image registration is a fundamental and ubiquitous task in both clinical and
research domains of the medical field, errors in registration can have serious consequences …

This technology report describes the longitudinal registration approach that we intend to
incorporate into SPM12. It essentially describes a group-wise intra-subject modeling …

The evaluation of ventricular function is important for the diagnosis of cardiovascular
diseases. It typically involves measurement of the left ventricular (LV) mass and LV cavity …

This paper presents a generative Bayesian model for diffeomorphic image registration and
atlas building. We develop an atlas estimation procedure that simultaneously estimates the …

Discrete optimisation strategies have a number of advantages over their continuous
counterparts for deformable registration of medical images. For example: it is not necessary …

Whole-body positron emission tomography-computed tomography (PET-CT) imaging in
oncology provides comprehensive information of each patient's disease status. However …

In settings where high-level inferences are made based on registered image data, the
registration uncertainty can contain important information. In this article, we propose a …

We investigate uncertainty quantification under a sparse Bayesian model of medical image
registration. Bayesian modelling has proven powerful to automate the tuning of registration …

An unsolved problem in medical image analysis is validation of methods. In this paper we
will focus on image registration and in particular on nonlinear image registration, which is …

We propose a novel variational Bayesian formulation for diffeomorphic non-rigid registration
of medical images, which learns in an unsupervised way a data-specific similarity metric …