A collaboration between mathematics, engineering, physics and biomedical scientists and clinicians, aiming to achieve synergies between applied mathematics and statistics through the focus on the analysis of clinical imaging.

We currently have 40 projects

Developing a multimodal imaging approach to characterize tumoral heterogeneity of advanced nasopharyngeal carcinoma

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Proximal-Nets: Unfolding Proximal Algorithms for Accelerating and Improving MR Image Reconstruction

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Joint Variational Reconstruction and Motion Estimation via Sparse Dictionary Learning for Robust Optical Flow

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Automated assessment of disease progression in Idiopathic Pulmonary Fibrosis

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Developing a Predictive Model Integrating Machine Learning and Image Inpainting to Delineate Tumour Invasion in Glioblastoma

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Multi-task Transfer Learning for Deep Convolutional Neural Network in Automatic Classification of Mammography

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Unsupervised Brain tumor and abnormality detection

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Fundamentals of models and sampling in undersampled acquisitions

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Undersampled Helium Atom Microscopy for resolution enhancement

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The Complete Inversion Formulation For EEG and MEG

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A-B quasiconvexity and imaging processing

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Numerical analysis of bi-level parameter training scheme in total variation image reconstruction

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Mapping zebrafish cell migration in vivo

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Flow of microtubules in the Drosophila oocyte

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Characterising blood flow in haemoglobin image sequences

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Cellular mechanics of Drosophila

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A Simultaneous Reconstruction and Motion Estimation Approach for Improving Undersampled MRI Reconstruction

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Restoring Specular-Free Video Sequences from Rank-Constrained Data

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Automated Classification of Osteoarthritis with Textural Analysis of Magnetic Resonance Images

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DeepCardio: towards a better prediction of heart attacks and stroke using a machine learning approach

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Radiomics: Calcium scoring and textural analysis for the prediction of heart attack and stroke

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Visualisation of bone asymmetry in CT data

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Computer-aided detection and personalised screening in breast imaging

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Multi-modal image analysis in cancer research

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Robustness of fMRI interpretations to modelling assumptions

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Joint reconstruction and segmentation from undersampled MRI data

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Mixed Effects Model of High-dimensional Irregular Shaped Tensors on Manifolds

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Learning Image Registration

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Electron Microscopy in Medical Research

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Learning a Sampling Pattern for MRI

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Photoacoustic tomography - Variational Methods for Improving Spatial Resolution

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Unsupervised analysis of tumour vascular parameters in photoacoustic tomography

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Fidelity enhancement in NMR spectroscopy for assisted drug design

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Super-Resolved Diffusion Tensor Imaging

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Faster PET Reconstruction by Stochastic Optimization

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Reconstruction of endoscopic images

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Image reconstruction from Fourier samples

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Feature extraction in high-dimensional data

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Numerical modelling of coronary atherosclerotic plaques

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Assessing the rupture risk of abdominal aortic aneurysm based on multi-modal clinical imaging

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