Date: Nov 26, 2024 (9 AM to 12 PM)
Location: The University of Western Australia
MATLAB offers many capabilities in flexible generalised end-to-end image analysis and AI workflows that can be applicable to different fields. This workshop focusses on the application of this workflow on medical and geological images; two different fields of studies with very common image formats, processing and AI techniques. In these applications, images come from multiple sources such as MRI, CT, X-ray, ultrasound, and PET/SPECT. Engineers and scientists must visualize and analyse multi-domain image data to extract meaningful information.
In this tutorial, we will explore how you can import image data and metadata, visualize them, register multiple scans from one or more sources, preprocess them, segment out areas of interest, label the data, train and use AI models on the data, and finally, how these can help you quantify and draw predictive conclusions from the data.
Examples will include:
Dr Emmanuel Blanchard is a senior application engineer at MathWorks who first joined the company as a training engineer in 2014. His main focus is on data analytics, which includes machine learning and deep learning, and image processing. He taught several MATLAB courses as well as specialized topics such as machine learning, statistics, optimization, image processing and parallel computing.
Prior to joining MathWorks, he was a Lecturer in Mechatronic Engineering at the University of Wollongong. He holds a PhD in Mechanical Engineering from Virginia Tech. He also worked as a Systems / Controls Engineer at Cummins Engine Company and as a research assistant in several research institutions in California and Virginia.
Research students, academics, and developers from industry.