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whole tumour while leaving in place as much healthy tissue as possible (tissue conserving surgery). This surgery is challenging because surgeons lack accurate imaging tools to assess the surgical margins
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expertise in machine learning and image processing, heritage scientists, conservators and curators. Summary of Project: In the cultural heritage sector, there is a long tradition of using complementary
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School of Engineering to deliver this ambitious research. Previous experience in optics, image processing and coding is desirable. Number of awards: 1 Start date: 22nd April 2024 Award duration: 3-years
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Modern deep learning techniques achieve human-like performance in many medical image analysis tasks, including the identification of anomalous tissue/pathology from medical scans. To be trained
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2024. The projects will be based around the development of advanced magnetic resonance techniques to optimise heterogenous catalysts and the operation of the reactor in which the catalysis occurs. Two
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opinion with a level of certainty to assist human experts. From the aspect of research methodology, the research work involves image processing, data analytics and machine learning, as well as image-based
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have the opportunity to apply machine learning image processing techniques to guide theory with experimental analyses. Your research will lead to new discoveries and a close interaction with our
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. The projects will be based around the development of advanced magnetic resonance techniques to optimise heterogenous catalysts and the operation of the reactor in which the catalysis occurs. Two projects
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at the Faculty of Engineering (FoE), University of Nottingham which conducts cutting-edge research into the development of imaging technology for biomedical applications. Vision We are seeking PhD students who
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an innovative technique called speckle contrast optical tomography (SCOT) with the potential to provide 3D images of cerebral blood flow in the infant brain. The main objectives are: To develop a small wearable