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Wednesday 6th December 2017

Centre for Mathematical Sciences

United Kingdom


Mathematical imaging, image processing and computer vision are fundamental for gaining information across numerous areas. The rapid development of new imaging hardware, the advance in medical imaging, the advent of multi-sensor data fusion and multimodal imaging, as well as the advances in computer vision have stimulated research leading to highly sophisticated and rigorous mathematical models and theories.

Recent advances have seen an explosion in the use of images in a variety of scientific and engineering applications. As this trend continues, the ever growing challenges in applications and technology constantly generate new demands that cannot be met by existing mathematical concepts and algorithms. Consequently, new mathematical models need to be developed in order to fully realise the potential of these advances.

Aims and Objectives

This one day workshop formed part of the Isaac Newton Institute Research Programme Variational Methods and Effective Algorithms for Imaging and Vision. It brought together mathematicians, statisticians, computer scientists and engineers from both the research and industry communities.

Imaging and vision is highly multidisciplinary – spanning mathematics, engineering, machine learning, computer vision and machine vision. There are numerous applications for this science in sectors such as medical imaging, security, geoscience, environment, food, manufacturing, agriculture, films, art and archeology.

As the science develops, there is increasing use of variational models, shapes and flows, differential geometry, optimisation theory, numerical analysis, statistical / Bayesian graphical models, and machine learning. This Open for Business workshop therefore aimed to extend the reach of the Isaac Newton Institute research programme and further foster exchange between different groups of researchers and practitioners involved in mathematical imaging science.

Talks from academics and end-users as well as discussions, explored the challenges as well as the new horizons in theory, models, techniques and applications of mathematical imaging and vision.  Presentations featured academic state-of-the-art talks, as well as end-user challenge type presentations and included areas such as:

  • Approaches to image reconstruction - generative models, parameter learning and sparsity
  • Shape analysis – optimisation, flows, mappings and shapes
  • Computational challenges in image processing
  • End-user challenge talks from areas including seismic imaging, food industry, archaeology and art, security sector, film industry and medical imaging.

The workshop included a poster exhibition, which ran during the lunch and the drinks/networking session and there was a short discussion and question session to finish. It brought together industrial and academic experts from a diverse set of backgrounds and areas.

Registration and Venue

The workshop took place at the Centre for Mathematical Sciences in Cambridge.