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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

Read more at: Anisotropic Interaction Models for Simulating Fingerprint Patterns

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 


Read more at: Anisotropic variational models and PDEs for inverse imaging problems

Anisotropic variational models and PDEs for inverse imaging problems

Researcher: Simone Parisotto, Carola-Bibiane Schönlieb

 


Read more at: Cellular Mechanics of Drosophila

Cellular Mechanics of Drosophila

Researcher: Lukas F. Lang, Jocelyn Étienne, Nilankur Dutta, Bénédicte Sanson, Elena Scarpa, Carola-Bibiane Schönlieb 


Read more at: Faster PET Reconstruction by Stochastic Optimisation

Faster PET Reconstruction by Stochastic Optimisation

Researcher: Matthias Ehrhardt, and Carola-Bibiane Schönlieb 


Read more at: Flow of Microtubules in the Drosophila Oocyte

Flow of Microtubules in the Drosophila Oocyte

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


Read more at: Geometric Integration Methods for Optimisation

Geometric Integration Methods for Optimisation

Researcher: Erlend Riis, and Carola-Bibiane Schönlieb


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

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

Reseacher: Angelica Aviles-Rivero, and Carola-Bibiane Schönlieb


Read more at: Inverse Problems with Imperfect Forward Models and Applications in Biomedical Imaging

Inverse Problems with Imperfect Forward Models and Applications in Biomedical Imaging

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


Read more at: Learning Sampling Patterns for MRI

Learning Sampling Patterns for MRI

Researcher: Ferdia Sherry, Erlend Riis, Luca Calatroni, and Carola-Bibiane Schönlieb


Read more at: Machine learning methods for segmentation of food microscopy images

Machine learning methods for segmentation of food microscopy images

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


Read more at: Mathematical challenges in electron tomography

Mathematical challenges in electron tomography

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


Read more at: Mathematics for Cultural Heritage Applications

Mathematics for Cultural Heritage Applications

Researchers: Simone Parisotto, Luca Calatroni, Rob Hocking, and Carola-Bibiane Schönlieb


Read more at: Model-Based and Deep Learning-Based Approaches for Image Restoration for Real-World Problems: Image Reflection Removal and Image Deraining.

Model-Based and Deep Learning-Based Approaches for Image Restoration for Real-World Problems: Image Reflection Removal and Image Deraining.

Researcher: Angelica I. Aviles-Rivero, and Carola-Bibiane Schönlieb


Read more at: Equivariant Neural Networks for Inverse Problems

Equivariant Neural Networks for Inverse Problems

Researchers: Ferdia Sherry, Christian Etmann, Matthias Ehrhardt, Elena Celledoni, Brynjulf Owren, and Carola-Bibiane Schönlieb 


Read more at: Multi-sensor Remote Sensing for the Detection of Individual Trees

Multi-sensor Remote Sensing for the Detection of Individual Trees

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


Read more at: Multi-Tasking Models for Image Analysis

Multi-Tasking Models for Image Analysis

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


Read more at: Semi-Supervised Hyperspectral Image Classification

Semi-Supervised Hyperspectral Image Classification

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

 


Read more at: Template-Based Image Reconstruction from Sparse Tomographic Data

Template-Based Image Reconstruction from Sparse Tomographic Data

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


Read more at: Tracking Tumour Dynamics

Tracking Tumour Dynamics

Principal Investigators: Thomas Buddenkotte, Subhadip Mukherjee, Carola-Bibiane Schönlieb and Evis Sala

This project has its own website.

 


Read more at: INTEGRAL: Robust and Efficient Analysis Approaches of Remote Imagery for Assessing Population and Forest Health in India

INTEGRAL: Robust and Efficient Analysis Approaches of Remote Imagery for Assessing Population and Forest Health in India

Researchers: Madeleine Kotzagiannidis, Angelica Aviles-Rivero, Rihuan Ke, Carola-Bibiane Schönlieb, David Coomes, James Woodcock, and Rahul Goel

This project has its own website.


Read more at: Plug-and-Play Proximal Algorithm for Inverse Imaging Problems

Plug-and-Play Proximal Algorithm for Inverse Imaging Problems

Researcher: Angelica Aviles-Rivero, Jingwei Liang, and Carola-Bibiane Schönlieb


Read more at: Unsupervised Learning for Image Analysis

Unsupervised Learning for Image Analysis

Researcher: Angelica Aviles-Rivero, Hankui Peng, Lihao Liu, and Carola-Bibiane Schönlieb


Read more at: Machine learning methods for segmentation of food microscopy images

Machine learning methods for segmentation of food microscopy images

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