Machine and Deep Learning for Medical Imaging with MATLAB
Tuesday, March 29, 2022
2:00 pm - 3:00 pm
About the Event
AI techniques are increasingly seen as powerful tools to address many complex problems. In this technical talk, we’ll explore in detail the workflow involved in developing and adapting machine and deep learning algorithms for medical image classification or segmentation problems using real-world case studies. Some of the tasks we’ll explore in this workflow are:
- Import and manage large sets of images without loading them into memory
- Build networks from scratch with a drag-and-drop interface of Deep Network Designer
- Perform classification tasks on images, and pixel-level semantic segmentation on images
- Semi-automate ground-truth labeling efforts to increase training dataset
- Understand hyperparameter tuning and why it’s important.
About the Speaker
Dr. Reza Fazel-Rezai is a Senior Customer Success Engineer at MathWorks. He received the BSc., M.Sc., and Ph.D. degrees in Electrical Engineering and Biomedical Engineering in 1990, 1993, and 1999, respectively. He has more than 20 years of experience in the industry as a senior research scientist and research team manager and academia as the founding Director and tenured Professor of Biomedical Engineering. He has published more than 150 scientific papers and edited 6 books in the field of biomedical engineering. His research interests include biomedical signal and image processing, brain-computer interface, seizure detection and prediction, neurofeedback, and human performance evaluation based on physiological signals using pattern recognition methods such as fractals and chaos theory, machine learning, and deep learning approaches.