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06 Apr

4D cone beam CT imaging of foot and ankle dynamics

Named Projects

4D cone beam CT imaging of foot and ankle dynamics

DEADLINE 2ND MAY 2017

Supervisors: Dr Marta Betcke (CMIC), Dr Andrew Goldberg (IoO, RNOH), Prof David Hawkes (CMIC) and Guy Long (CurveBeam Europe Ltd)

Duration: 3 years, IMPACT Studentship CMIC, Institute of Orthopaedics, RNOH, CurveBeam LLC
Eligibility: UK or EU nationals

Description:
The foot and ankle are complex structures comprising 28 bones and the structure reflects the complexity of activity for movement, shock absorption stability and balance. Successful diagnosis and treatment planning can be extremely difficult due to limitations posed by existing imaging modalities. Understanding the complex 3D motion of the foot and ankle joints is vital in assessing the progression of long term diseases such as arthritis and devising new treatments for both injury and disease of the ankle and foot.

A new low dose vertical axis cone beam CT scanner, pedCAT, has been developed by CurveBeam, which unique feature is the ability to provide 3D images of the weight bearing foot and ankle with the patient standing motionless in a natural standing position. The aim of the PhD project is to develop and implement imaging protocols and reconstruction algorithms for imaging of dynamic function under load with the pedCAT scanner.

To this end, the candidate will mathematically formulate the associated dynamic inverse problem (DIP) and investigate under which conditions and with what additional information the DIP can be uniquely and stably solved. An example of such additional information would be a static scan, which would help to reduce the dimensionality of the problem. Another direction of investigation is use of techniques from machine learning to take advantage of other patient as well as simulated data sets in the reconstruction. The candidate will devise data acquisition protocols and image reconstruction algorithms for the proposed scenarios.

The outcomes of the PhD will provide insight whether the existing hardware equipped with the new imaging protocols and software is capable of extracting all the clinically relevant information or a new dedicated dynamic foot scanner needs to be developed.

Person specification:
• A BSc or MSc degree in Mathematics, Scientific Computing, Computer Science or related field with top marks
• Experience with numerical algorithms, scientific computing
• Ability to rigorously formulate ideas as mathematical problems
• Programming skills, knowledge of Matlab and C++
• Previous experience with image reconstruction and registration, in particular with cone beam X-ray imaging and limited angle problems would be beneficial
• Interest in image reconstruction and inverse problems research involving both Mathematics and Computer Science
• Good communication skills; especially in written English
• Strong work ethic and the ability to think creatively and independently

Apply To apply please send a copy of your CV and expression of interest to Dr Marta Betcke m.betcke@ucl.ac.uk

DEADLINE 2ND MAY 2017