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Image Processing in MATLAB Workshop

Overview

This workshop is designed for participants who have a foundational understanding of programming and are interested in learning about image processing in MATLAB. The workshop will cover working with image data, segmenting and performing structural analyses on features of interest, and visualizing analysis results. By the end of this hands-on experience, participants will have a strong understanding of manipulating image data, executing image processing pipelines, and designing impactful result plots.

Requirements

  1. Students must have MATLAB installed and functioning on their laptop.
  2. Students are expected to have a basic level of understanding of programming concepts (ex. syntax, writing and running a script, variables, for loops, if/else statements, creating and calling functions, etc.).

Software

Outline

  1. Module I: Intro to Image Data in MATLAB (30 min)
    a. What is an image?

    • Understand how images are represented in MATLAB
      b. Image programming basics
    • Reading in, viewing, and saving image data
      c. Activity I – Read in, format, and view an image (20 min)
  2. Module II: Pre-processing and Segmenting Image Data (1 hr 15 min)
    a. What is pre-processing?

    • Importance and techniques
      b. What is segmentation?
    • Importance and techniques
      c. Activity II – Segment a feature of interest (1 hr)
  3. Module III: Performing Image Analyses (30 min)
    a. What is structural image analysis?

    • Different types of analyses you can perform on a segmented feature
    • Combining functions to perform a desired structural analysis
      b. Activity III – Perform structural analysis on a feature of interest (20 min)
  4. Module IV: Visualize Image Analysis Results (45 min)
    a. Plotting basics

    • Plotting syntax
    • Common built-in plotting functions
    • Customizing plots to best display results
      b. Activity IV – Visualize image analysis results (35 min)

References

Material created by Megan Ng

Workshop created as part of the McGill Initiative in Computational Medicine

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