Data Analytics and Medical Image Processing with MATLAB

Location: Max Planck Institute for Brain Research
Venue: Lecture Hall
Date: October 8th, 2015
Time: 09:30 - 15:00


MATLAB® is a high-level language and interactive environment for numerical computation, visualization, and programming. In this seminar we will be how MATLAB will help you to process, visualize, and quantify your experimental data as well as biomedical images.

Using examples of medical applications, we will first demonstrate how you can leverage MATLAB to explore your data and make predictions using machine learning techniques such as neural networks.

Furthermore, you will learn about to use computer vision to detect objects in images as well as classify images using new functionalities for feature extraction, pattern recognition and classification, handling large sets of images.

Finally, we will demonstrate simple ways to improve and optimize your code that can boost execution speed. We will also address common pitfalls in writing MATLAB code, explore the use of the MATLAB Profiler to find bottlenecks, and introduce programming constructs to solve computationally and data-intensive problems on multicore computers, clusters and GPUs.

Highlights include:

  • Accessing, exploring, analyzing, and visualizing data in MATLAB
  • Training, evaluating and comparing a range of machine learning models such neural networks to build predictive models
  • Handling a large set of images
  • Automatic object recognition and tracking
  • Feature extraction and Image classification
  • Optimizing the performance of your MATLAB code


Time Title
09:00 Registration
09:30 Introduction
09:45 Exploratory and predictive data analytics
  • Data import and visualization
  • Tools for algorithm development
  • Predictive modelling using machine learning techniques
11:00 Break
11:15 Medical Image processing and Computer Vision
  • Image enhancement and registration
  • Classification of images
  • Object tracking
12:30 Lunch break
13:30 Speeding up your MATLAB code
  • Performance optimization of serial code
  • Techniques for explicit parallelization
  • Automatic generation of standalone C code
14:45 Conclusion
15:00 End
Data Analytics and Medical Image Processing with MATLAB

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