Keywords: Diagnosis/Prediction, Radiomics
Motivation: Radiomics has potential to bring added values to cancer diagnosis and prognosis, whilst a practical tool that is accessible for clinicians and radiologists has not been available.
Goal(s): To design MIROR, a clinical decision support system, that can aid tumour diagnosis with real-time image and spectroscopy analysis.
Approach: The project keeps collecting childhood brain tumour proton MR images and spectroscopy in England and has built a multi-centre database that includes 377 cases.
Results: MIROR supports key features including visualisation, image analysis, feature extraction, spectroscopy quantification, and tumour type and subtype prediction through machine learning.
Impact: A practical solution that translates radiomics and machine learning into clinical scenarios can aid tumour diagnosis and treatment planning, bring benefits to patient healthcare, and improve clinical outcomes.
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