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person. Aims: The project aims to develop and evaluate AI methods for medical image analysis to detect diabetic retinopathy, glaucoma, cataract and age-related macular degeneration (AMD). As
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arrhythmias, and 900,000 with heart failure. Medical imaging techniques, such as CT, MRI, and X-ray, are vital for diagnosing and guiding the treatment of cardiovascular diseases. This project aims to develop a
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between the labs of Prof. Notingher (expertise in Raman spectroscopy), Dr. Gordon (Optical Fibre Imaging) and Dr Mohammad (snake-like medical robots). For further information: please contact Ioan Notingher
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Methods Soft lithography and microfabrication to create defined surface landscapes. • Mating assays between resistant and sensitive Enterobacteriaceae strains. • Live-cell imaging and fluorescent plasmid
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practical solutions for safer participation. Projects may be supervised or co-supervised by experts from Engineering Science and the Medical Sciences Division. Potential Supervisors: Prof. Thomas Okell, Prof
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Scoliosis (AIS). Although surgery straightens the spine, AIS is associated with poor self-image and psychological distress. This project will investigate this, developing assessment and management tools
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focus on the medical image processing aspect of the Birth4Cast simulator by researching and developing automated image segmentation procedures to extract the pelvic floor muscle complex and the fetal head
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have the opportunity to develop their computational modelling capabilities in this project, alongside learning new skills such as testing on biological tissues and medical image processing
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Revolutionising Infection Diagnosis Through Targeted Radiometal Imaging Background of the Project: People with conditions like heart disease, diabetes, cancer, organ transplants
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Revolutionising Infection Diagnosis Through Targeted Radiometal Imaging Background of the Project: People with conditions like heart disease, diabetes, cancer, organ transplants