Motion compensation for multi-modal and multi-parametric preclinical imaging


Contact Professor Daniel Lesnic (Applied Mathematics); Dr Charalampos Tsoumpas (Medicine); Professor Jurgen Schneider (Leeds Institute of Cardiovascular and Metabolic Medicine (LICAMM), and Dr Matteo Milanesi (Bruker UK Ltd. – Industrial Partner) to discuss this project further informally.

Project description

In the imaging industry there is a continuous pressing need to satisfy consumer, customer and competition requirements. This is possible only if appropriate leading edge medical imaging innovation/technology is modelled, verified and validated by the combined effort of the academics (in this project,  applied mathematics and biomedical imaging) and industrialists (in this project, leading edge provider of imaging instruments) through the proposed CASE Award project.

The preclinical imaging industry

The industrial participant in this Industrial CASE is represented by the company Bruker UK Ltd., which is a main preclinical imaging enterprise capable of delivering high quality multi-modal medical imaging technologies, especially for small animal research. The company sees the commercial exploitation and development of cutting-edge mathematical and medical modelling tools and methodologies, as a very important component of their R&D strategy for driven innovation, growth and increasing competitiveness. The combined application of inverse problems and imaging to be developed by this studentship will provide experience for the graduate student in a growing and strategically important Mathematics for Medicine discipline for high-value healthcare manufacturing.

The current project proposes to study motion correction and cross-platform registration for such multi-modal (positron emission tomography (PET), X-ray computed tomography (CT) and magnetic resonance imaging (MRI). Success of this project will significantly improve the resolution and diagnostic value of images.

Project objectives

The project will investigate and assess the combined functional imaging capabilities of the aforementioned imaging modalities with experimental data provided by the scanners manufactured by the industrial partner, in the desire to improve the measurement of biological processes at the molecular levels in small animals, and to identify sites of disease within their anatomical reference. In particular, multi-modal registration and motion correction strategies will be investigated in order to derive spatially registered images independent of respiratory and cardiac motion. Such techniques take supplementary and non-redundant information from the MRI, CT and PET data itself or an external monitoring device, such as electro-cardiogram (ECG) and respiratory tracking system. The student will invert this noisy measurement information using state-of-the-art multi-modal image registration and reconstruction techniques, e.g. the structural joint inversion with regularization, in order to obtain stable and robust solutions and translate them into preclinical and potentially clinical practice. 

Impact of research to advanced imaging centres & pharmaceutical industries

Pharmaceutical industry establishes preclinical imaging facilities for the swift development of more precise drugs and therapeutic strategies. The improvement of accuracy in diagnosis and quantification achieved by inverting multi-modal measurements will improve the quality and reliability/credibility of the findings benefiting the pharmaceutical industry.


In addition to attending the University of Leeds training programme for PhD students, the  student would benefit from training on use of the Bruker scanning equipment available at the Experimental and Preclinical Imaging Centre (ePIC) in the  LIGHT Laboratories at Leeds University.

Entry requirements

The project requires a dedicated, motivated, talented first-class student with a solid background in applied mathematics or physics (or equivalent), and ideally in medical imaging. Computational programming skills are highly desired

How to apply

Please send a CV and a short ‘statement of motivation’ to Professor Daniel Lesnic. Further information will then be provided. Deadline for applications is 15 March 2018. The scholarship is due to start on 1 October 2018.