Transforming dental imaging using optical coherence tomography

The successful candidate will join the UCL CDT in Intelligent, Integrated Imaging in Healthcare (i4health) cohort and benefit from the activities and events organised by the centre.

Project Background: 

This project will use Optical Coherence Tomography (OCT) to revolutionise general dentistry, which urgently needs superior in vivo imaging. For example, although dental caries affects more than 90% of adults, the current gold standard of visual inspection and X-ray radiography detects only around 67% of caries. Furthermore, there is currently no imaging technique at all available for diagnosing periodontal diseases.

OCT is a high resolution, three-dimensional, non-ionising, imaging technique widely used in ophthalmology. It is highly sensitive to subtle changes in soft and hard tissue microstructure which allows for earlier detection of dental disease, monitoring treatment responses over shorter time scales and enables personalised treatments.

The UCL Eastman Dental Institute (EDI) is a center of excellence for post-graduate education and clinical research. Research at the EDI has revealed promising evidence regarding the clinical use of OCT in the oral cavity. This project seeks to translate OCT into a routine clinical tool in three steps: identify the most promising clinical applications; optimizing hardware and imaging protocols; and developing bespoke image analysis tools. This work will be key to OCT becoming a mainstream imaging tool in general dentistry.

Research aims: 

1. Work with clinicians including to establish the clinical applications most likely to be impacted by OCT.
2. Optimise the hardware and develop an imaging protocol. The student will apply understanding of OCT image formation and clinical requirements to develop an imaging protocol.
3. Develop bespoke imaging segmentation and analysis tool for the oral cavity 
4. Investigate the use of quantitative approaches to OCT imaging such as parametric imaging which have been used in other biomedical applications to differentiate between tissue types.
5. Demonstrate the above in a clinical setting.

Application Details:

This studentship is only open to Home Fee paying applicants. 

Applicants are generally expected to have, or expect to obtain, a UK first class or 2:1 honours degree (or equivalent international qualifications or experience) in physics, engineering, mathematics or related subjects. Applicants must have an interest in applying their skills in clinical settings.

Applicants should demonstrate all of the following skills and attributes:

• Coding in high level languages such as Matlab and Python.
• A working knowledge optical imaging or optical coherence tomography.
• Excellent verbal and written communication skills.
• Willingness to take initiative and lead.
• Ability to work independently and in a team.

Applicants should also demonstrate some of the following desirable skills:

• Experience with image analysis and segmentation.
• Background in rapid prototyping such as by CAD and 3D printing.
• Experience with machine learning.

How to apply:

Please complete the following steps to apply.

• Send an expression of interest and current CV to: [Email Address Removed] and [Email Address Removed]]

Please quote Project Code: 22002 in the email subject line.

• Make a formal application to via the UCL application portal https://www.ucl.ac.uk/prospective-students/graduate/apply . Please select the programme code Medical Imaging TMRMEISING01 and enter Project Code 22002 under ‘Name of Award 1’ 

Application Deadline: 18 February 2022

If shortlisted, you will be invited for an interview.