First Part: Footpath to the brain: a radiologist’s journey into neuroscience research
Godwin Ogbole
Abstract
In this session, I’ll share my academic and professional experiences in Nigeria, including medical school and residency training. The pathway I travelled, describing the ‘road signs and travel guides that led me to neuroscience research. I’ll talk about the challenges I experienced, how I overcame some of them. I’ll discuss my present research interests as well as my long-term research goals.

Second Part: Computational Magnetic Resonance Imaging: The Nigerian Story
Michael Dada
Abstract
No single neuroimaging technique currently lends itself to easy, reliable and consistent use in day-to-day settings to differentiate intra-axial brain tumours based on origin and histopathologic grading. Tissue discrimination is a more significant challenge after treatment, because pseudo-progression, pseudo-response and development of radiation necrosis are real possibilities. In this chapter we have demonstrated practical ways in which computational MRI can be used to provide innovative data-driven algorithms for the prediction, simplification and characterization of brain tumours as well as to delineate their intrinsic mechanisms based on Bloch’s Nuclear Magnetic Resonance (NMR) flow equation, Bessel functions and Bessel properties. The results have motivated data-driven predictions required for statistical learning or machine learning and have led to the application of deep learning for the classification of brain tumours. These can help significantly to accurately delineate tumour margins in order to ensure appropriate diagnosis, treatment and prognostic information for early differentiation between primary and metastatic malignant brain tumours. In this presentation, the historic development of computational magnetic resonance imaging has been outlined.