Michela Antonelli started her research career as a member of the Computational Intelligence Group at the Department of Information Engineering (University of Pisa). During her PhD studies, she was involved in the development of a Computer-Aided Diagnosis (CAD) system able to automatically detect and diagnose lung nodules in CT scans. After the PhD, her research interests moved to the field of Multi-Objective Evolutionary Fuzzy Systems (MOEFSs). MOEFSs deal with the hybridization of Fuzzy Rule-based Systems (FRBSs) and Multi-Objective Evolutionary Algorithms (MOEAs), to design FRBSs which are both accurate and interpretable. In this field, she has produced a considerable number of publications in peer-reviewed journals of high impact factor and selective international conferences. From January 2015 her focus returned to medical imaging and she joined the Translational Imaging Group at University College London working on the development of a Computer Aided Detection system for prostate cancer detection and diagnosis in mp-MRI. In May 2019 she joined the School of Biomedical Engineering & Imaging Sciences, at King’s College London, working on new machine learning based medical image analysis methods for the active surveillance (AS) of patients with prostate cancer. The management of early prostate cancer is challenging due to the difficult task of distinguishing patients with clinically relevant cancers from those whose “disease” is destined merely to be an incidental histological event. This project aims to investigate changes in the appearance of lesions in multiparametric Magnetic Resonance Imaging data for patients undergoing AS to predict prostate cancer behaviour and to avoid unnecessary radical treatments.
ProjectsCancer - Prostate
Decision fusion of 3D convolutional neural networks to triage patients with suspected prostate cancer using volumetric biparametric MRI
Mehta, P., Antonelli, M., Ahmed, H., Emberton, M., Punwani, S. and Ourselin, S., 2020, In Medical Imaging 2020: Computer-Aided Diagnosis (Vol. 11314, p. 1131433). International Society for Optics and Photonics.