Information on two on-line, free of charge workshops demonstrating how Deep Learning and MATLAB tools can be used with medical images. Introduction to Deep Learning for Medical Imaging-online course The Row Fogo Centre for Research into Ageing and the Brain in collaboration with MathWorks delivered two 1-day live-streamed courses on the 28th April and 11th May 2020. In this hands-on workshop, Deep Learning was gently introduced to course participants and demonstrated how MATLAB tools can be used with medical images. Both workshops were fully booked and received high interest from the local and international research community. Course highlights Learn the fundamental theory of Deep Learning for classification and regression problems Learn the Deep Learning workflow in MATLAB Access and explore various pre-trained models Use transfer learning to build a network for image classification Learn how to evaluate the network and improve its accuracy Explore examples of Deep Learning in Medical Imaging Agenda Session 1 Times Session 2 Times Topic 08:30-09:30 15:00-16:00 Theoretical Background 09:30-10:30 16:00-17:00 Using MATLAB for Deep Learning 10:30-11:30 17:00-18:00 Example for Medical Imaging Applications Additional information The session aimed at all who are interested in practical applications of Deep Learning in the medical field. Both sessions covered the same materials. Basic knowledge in MATLAB was required. Free 2 hours MATLAB Onramp course was recommended to those without previous knowledge. About the Presenters Dr Maria Valdes Hernandez is the Row Fogo Lecturer in Medical Image Analysis at the University of Edinburgh. She has a background in Electronic Engineering and software development for industrial, mobile and clinical research applications. She is also a Fellow of the High Education Academy and Leader of the Image Analysis and Image Processing Techniques courses offered by the MSc online Programmes of the Edinburgh Imaging Academy. Dr Maria Valdes Hernandez - University of Edinburgh profile Dr Julia Hoerner is the EMEA Deep Learning Academic Liaison Manager at MathWorks in Cambridge. She has a background in engineering, renewable energy and energy consumption. She worked on energy forecasting using deep learning at the University of Reading and University of Strathclyde. Dr Martina Sciola is a Technical Specialist Engineer at MathWorks, supporting teaching and research with MATLAB and Simulink at Universities in UK and Ireland. She is a Biomedical Engineer and graduated at the University of Sheffield with a PhD on personalised cardiovascular modelling. She also had the opportunity to work as research associate for diagnosis of Pulmonary Hypertension and as research coordinator for an EU project to establish a new centre of excellence of medicine. Further details MATLAB and Simulink Training website Publication date 12 Aug, 2020
