A new research centre will force mathematicians and statisticians to work together on medical images, dissolving the traditional boundary between their fields. Current medical imaging—from brain scans to heart ultrasounds to tumour biopsies—produces data at vastly different scales, from individual cells to whole organs. No single mathematical approach can handle this complexity. Statisticians and applied mathematicians typically operate in separate silos, each developing tools the other cannot use. This means clinicians often analyse each image type in isolation, missing the full picture of a patient’s condition. The centre aims to create a unified mathematical framework that combines high-dimensional statistics with computational numerical analysis. If successful, it will allow doctors to integrate all available imaging data—cellular, tissue-level, and whole-organ—into a single holistic analysis. This could improve diagnosis, prognosis, and treatment planning for cancer, heart disease, and neurological disorders. The work is primarily fundamental science, developing new mathematical frontiers rather than immediate clinical tools. But past breakthroughs in applied mathematics—from CT scan reconstruction to MRI signal processing—show how such foundational research can quietly transform medical diagnostics.
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Applied Mathematics and Statistics are routinely seen as separate disciplines. However, many of the methodological challenges in image analysis, particularly from the types of multiscale multimodal images available from Neurological, Cardiovascular and Oncology imaging, illustrate that a combined approach, dissolving intradisciplinary mathematical boundaries, is the only possible way forward if a step-change in image analysis of combined data is to occur. This Centre will foster links between applied maths and statistics, particularly high dimensional and functional statistical analysis with applied and computational numerical analysis, through the focus on multimodal imaging data. The Centre proposes to provide a research focus on bringing state-of-the-art mathematical tools to clinical end users through collaborations both within mathematics and between mathematics and healthcare professionals, particularly those in oncology, cardiovascular medicine and neurology. This will ultimately lead to new mathematical frontiers, joining statistics and computational mathematics, as well as a move away from individual image analysis to a holistic approach to all available imaging, from the cellular to systems scale, for clinical diagnosis, prognosis and treatment planning.
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