Research project

Medical Image Processing

Project overview

Engineering and Physical Sciences Research Council Studentship Award, EPSRC Grant number 1511465.
Medical surgeons treating patients with tumours, test tissue samples on the presence of cancer cells during the operation. In order to decide on a diagnosis, pathologists need to quickly analyse these tissue samples. They have the option of comparing the tissue against specimens from past cases, which are stored as physical wax models. This comparison is a time consuming process and because of that pathologists usually rely on cases they have seen before. This wastes the potential of the stored samples and may hinder the doctor from choosing the best possible treatment. Digitalizing the large amounts of wax samples, would allow quickly searching through them and provide the pathologist a selection of samples similar to the one he analyses.
The aim of this project is to automatize this digitalization of hospitals lung specimens and develop the underlying tools, technologies and platforms to do this. Furthermore a way of arranging them in a database is to be found and efficient comparison of new cases against the ones from the database is needed. Successful (or unsuccessful) treatment of these similar cases is to be presented to doctors.


Lead researcher

Professor Simon Cox

Head of Department

Research interests

  • My research focusses on computational tools, technologies and platforms and how they enable interdisciplinary problems to be solved in engineering and science.His team in the Computational Engineering and Design Group is applying and developing high performance and cloud computing in a variety of collaborative interdisciplinary computational science and engineering projects. These include:
  • High Performance and novel Computing SystemsCloud Computing and commercial distributed computing - which led to a spin out companyApplied computational algorithms Computational electromagnetics– which led to the formation of a spin-off company.New algorithms such as meshless methods and fast solvers.Data Management Simon is also Director of the Microsoft Institute for High Performance computing where he demonstrates why, where and how current and future Microsoft tools and technologies can be exploited to enable engineering and scientific research to deliver faster, cheaper and better results.
Connect with Simon

Research outputs

Lasse Wollatz, Mark Scott, Steven J. Johnston, Peter M. Lackie & Simon J. Cox, 2018
Type: conference
Lasse Wollatz, Steven Frampton, Kasia Konieczny, Tim Mitchell, Steven J. Johnston, Simon J. Cox, Andrea Burgess & Hasnaa Ismail Ismail-Koch, 2018
Type: conference
Lasse Wollatz, Steven J. Johnston, Peter M. Lackie & Simon J. Cox, 2017, Journal of Digital Imaging, 30(6), 772-781
Type: article
Lasse Wollatz, Kasia Konieczny, Clive Vandervelde, Tim Mitchell, Simon J. Cox, Andrea Burgess & Hasnaa Ismail-Koch, 2016
Type: conference
Lasse Wollatz, Simon J. Cox & Steven J. Johnston, 2015
Type: conference