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Algorithms for automatic analysis of radiographs of the knee with applications in diagnosis and monitoring of osteoarthritis



Important description
Osteoarthritis (OA) is the most common form of joint disease causing significant pain and disability. Studies have shown that the shape of certain joints is associated with the likelihood of getting OA, and the way in which the disease progresses.

This PhD aims to develop automatic software capable of locating the structures visible on radiographs of the knee, in particular the heads of the femur and tibia, and to analyse both the shape and appearance of the bones to look for correlations with disease and disease progression. The project will take advantage of state-of-the-art algorithms for modelling and matching bones developed within the group. It will focus on analysing images from large existing datasets, each containing images of thousands of patients either with OA or at risk of developing OA. Without the automatic systems to be developed it would be impractical to take full advantage of these datasets, as they include over 20,000 individual images.

The key outcomes of the research would be:

- Novel techniques for modelling and matching structures in radiographs
- A tool for automatically locating structures in radiographs of the knee, making accurate measurements and predicting outcome
- A better understanding of the relationship between bone shape/appearance and the likelihood of developing OA or its progression.

This 3-year full-time studentship will provide full support for tuition fees, an annual tax-free stipend of £13, 590 and cover all research expenses.

Extensive training will be provided in computer vision, medical image analysis, statistical analysis, software development and programming. The study will be conducted within the Centre for Musculoskeletal Research, an internationally recognised hub of musculoskeletal expertise, comprising over twenty existing PhD researchers.

Upon completion, the PhD would provide an excellent grounding for progression into a computer vision/medical imaging postdoctoral role within academia or industrial R&D.

Applicants should hold (or expect to obtain) a minimum upper-second honours degree (or equivalent) in mathematics, physics, computer science or related area. A Masters degree in a similar area would be an advantage as would previous experience of programming and/or computer vision techniques.

The project is available to UK/EU nationals only due to the nature of the funding and is due to start September 2013.

Please direct applications in the following format to Professor Tim Cootes (tim.cootes@manchester.ac.uk):

• Academic CV
• Official academic transcripts
• Contact details for two suitable referees
• A personal statement (750 words maximum) outlining your suitability for the study, what you hope to achieve from the PhD and your research experience to date.


Eligibility and other criteria
(European/UK Students Only)
This research project is one of a number of projects at this institution. It is in competition for funding with one or more of these projects. Usually the project which receives the best applicant will be awarded the funding. The funding is available to citizens of a number of European countries (including the UK). In most cases this will include all EU nationals. However full funding may not be available to all applicants and you should read the full department and project details for further information.


Application deadline
* 18 February 2013


Additional information, and important URL
http://www.medicine.manchester.ac.uk/musculoskeletal/
http://www.population-health.manchester.ac.uk/staff/TimCootes

Any enquiries relating to the project and/or suitability should be directed to Professor Cootes at the address above. Deadline for applications: 18 February 2013

http://www.medicine.manchester.ac.uk/musculoskeletal/
http://www.population-health.manchester.ac.uk/staff/TimCootes


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