Application Deadline: 11th December 2022
A 4 year funded PhD studentship is available as part of a long-term collaboration between the Institute of Nuclear Medicine (UCL and UCLH), the Centre for Medical Image Computing (UCL) and GE Healthcare.
Positron Emission Tomography (PET) imaging forms a crucial part of managing the patient’s treatment pathway in cancer and many other diseases. However, due to limitations on radioactive dose to the patient, PET images can be noisy and with relatively low image resolution. Modern PET scanners have experimental capabilities to measure gamma photon energy information in much more detail than before, which has the potential to increase signal to noise (SNR) ratio, as shown in preliminary scientific papers. However, further work is needed before this can be progressed to commercial systems.
This studentship aims to evaluate the impact of various methods to exploit additional photon energy information on image quality, as well as optimise the most promising candidates. Aspects to be included are scatter rejection by using energy window tuning, photon scatter estimation, accidental coincidences, as well as image reconstruction strategies. We envisage combining established PET data processing with novel techniques using Machine Learning.
Methods will be evaluated on Monte Carlo simulations as well as real PET measurements.
For further details regarding this PhD studentship can be found here:
https://www.ucl.ac.uk/intelligent-imaging-healthcare/case-studies/2022/nov/exploiting-photon-energy-information-positron-emission-tomography
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