Introduction to Deep Learning for Medical Imaging- Free Online One-Day Course (28 April 2020)
Introduction to Deep Learning for Medical Imaging- Free Online Course
Date/ Timeline: 28th April 2020 (1-day course)
| Start Time (CET) | End Time (CET) | |
| Session 1 | 08:30 | 11:30 |
| Session 2 | 15:00 | 18:00 |
Registration Link: https://uk.mathworks.com/mwaccount/register
Overview:
Please join us at this upcoming workshop which will be live streamed.
In this hands-on workshop we gently introduce you to Deep Learning and demonstrate how MATLAB tools can be used with medical images.
Highlights
- Learn the fundamental theory of Deep Learning for classification and regression problems
- Learn the Deep Learning workflow in MATLAB
- Access and explore various pretrained 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 |
Who Should Attend
The session is aimed at all who are interested in practical applications of Deep Learning in the medical field. Both sessions will cover the same materials, so please register only for one session. Please also register if you are attending remotely.
Attendees are required to create a MathWorks account with their university email address.
Further details can be found here: https://www.mathworks.com/mwaccount/register.
Basic knowledge in MATLAB is required. If you don't have previous knowledge, we recommend doing the free 2 hours MATLAB Onramp course.
Further details can be found here: https://www.mathworks.com/learn/tutorials/matlab-onramp.html.
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 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 https://uk.mathworks.com/learn/tutorials/matlab-onramp.html