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(GIF Created by Philip Sellars)

We are interested in all aspects of mathematical imaging: the use of mathematical techniques to analyse and to improve real-world images, ranging from photographs made with consumer cameras to the images made with professional imaging devices in the sciences and medicine. These include techniques such as MRI (magnetic resonance imaging) and PET (positron emission tomography). Our current research concentrates in particular on higher order PDEs for image inpainting, and discontinuity-preserving higher-order variational approaches for the recovery of sparsely sampled data. Further themes include parameter learning, with the goal of building "black box" imaging tools suitable for use by non-professionals.

Listed below are ongoing and previous projects in alphabetical order as well as funding sources. For categorised projects, follow the links on the left.

Research Projects

Anisotropic Interaction Models for Simulating Fingerprint Patterns

Researcher: Martin Burger, José Carrillo, Bertram Düring, Carsten Gottschlich, Stephan Huckemann, Lisa Maria Kreusser, Peter Markowich, Carola-Bibiane Schönlieb 

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Cellular Mechanics of Drosophila

Researcher: Lukas F. Lang, Jocelyn Étienne, Nilankur Dutta, Bénédicte Sanson, Elena Scarpa

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Continuum Limits in Graphical Based Machine Learning Problems

Researcher: Matthew Thorpe, Jeff Calder, Riccardo Cristoferi, Olly Crook, Matt Cunlop, Nicolás García Trillos, Tim Hurst, Ryan Murray, Carola-Bibiane Schönlieb, Dejan Slepcev, Andrew Stuart, Florian Theil, Kostas Zygalakis

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Flow of Microtubules in the Drosophila Oocyte

Researcher: Lukas F. Lang, Maik Drechsler, Hendrik Dirks, Martin Burger, Carola-Bibiane Schönlieb, Isabel M. Palacios

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Image Classification Under Minimal Supervision: Graph-Based Semi-Supervised Learning for Real-World Large-Scale Problems.

Reseacher: Angelica I. Aviles-Rivero, N. Papadakis (IMB, Université Bordeaux), R. Li (NUS), RT Tan (Yale-NUS), SM Alsaleh (GWU), P. Sellars (DAMTP, University of Cambridge), Q. Fan (Stanford University), C-B Schönlieb (DAMTP, University of Cambridge)

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Inverse Problems with Imperfect Forward Models and Applications in Biomedical Imaging

Researcher: Yury Korolev, Martin Burger, Carola-Bibiane Schönlieb, Leila Muresan

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Machine learning methods for segmentation of food microscopy images

Researcher: Rihuan Ke, Carola-Bibiane Schönlieb and Peter Schuetz

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Mathematical challenges in electron tomography

Researchers: Rob Tovey, M. Benning, C.-B. Schönlieb, O. Öktem, C.E. Yarman

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Model Selection by Bilevel Optimisation

Researchers: Ferdia Sherry, Erlend Riis, Luca Calatroni

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Multi-sensor Remote Sensing for the Detection of Individual Trees

Researchers: Jonathan Williams, Carola-Bibiane Schönlieb, Tom Swinfield, David A. Coomes, Juheon Lee, Xiaohao Cai

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Multi-tasking to Correct: Motion-Compensated MRI via Joint Reconstruction and Registration

Researcher: Veronica Corona, Angelica I. Aviles-Rivero, Noémie Debroux, Carola-Bibiane Schönlieb

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Semi-Supervised Hyperspectral Image Classification

Researcher: Philip Sellars, Angelica I. Aviles-Rivero, David Coomes, Nicolas Papadakis, Carola-Bibiane Schönlieb


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Template-Based Image Reconstruction from Sparse Tomographic Data

Researcher: Lukas F. Lang, Sebastian Neumayer, Ozan Öktem, Carola-Bibiane Schönlieb

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Variational Multi-task Methods for Improving MRI Reconstruction.

Researcher: Angelica I. Aviles-Rivero, Noémie Debroux, Veronica Corona, M. Graves, G. Williams, C. Le Guyader, Carola-Bibiane Schönlieb

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