Biomedical Imaging and Deep Learning Overview for Medical Devices

Overview

Deep Learning is a key technology driving the current Artificial Intelligence (AI) megatrend. You may have heard of some mainstream applications of deep learning, but how many of them would you consider applying to your medical imaging applications?

 

 

The aim of the session is to provide an overview of how MATLAB enables you to take advantage of disruptive technologies like deep learning. We'll explore, in detail, the workflow involved in developing and adapting a deep learning algorithm for medical image segmentation problem using the real-world case study of classifying parasitology slides.

 

Topics include:

  • Semi-Automating Ground Truth Image Labeling
  •  Automated feature extraction from images.
  • Generating optimized native embedded CUDA/C++ code.

 

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Speaker

Akhilesh Mishra


Akhilesh Mishra is currently the  Senior Application Engineer for the Medical devices and Healthcare industry at MathWorks Inc.. He specializes in the signal/data processing, artificial intelligence and GPU computing workflows. He has been with MathWorks since 2016. Akhilesh holds a M.S. degree from University of Kansas where he was the signal processing lead in a group working on radar and sonar systems for sounding the ice sheets of Greenland and Antarctica to study global sea-level rise.

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