Exercises

Throughout the MIA Lab, you'll complete several practical exercises to build your skills and prepare for the main project.

Exercise 1: Image basics

Due: Week 3

Learn the fundamentals of working with medical images:

• Reading and writing medical image files
• Understanding image properties (dimensions, spacing, origin)
• Basic image manipulation and visualization
• Working with SimpleITK

Detailed instructions

Starter repository

Exercise 2: Pipeline

Due: Week 4

Implement key components of the image processing pipeline:

• Pre-processing steps
• Registration between images
• Post-processing operations
• Integrating components into a workflow

Detailed instructions

Starter repository

Exercise 3: Random forest

Due: Week 5

Apply machine learning to medical image analysis:

• Feature extraction from images
• Training a random forest classifier
• Making predictions on new data
• Evaluating classifier performance

Detailed instructions

Starter repository

How to submit

GitHub Classroom is no longer used. For each exercise:

1. Open the starter repository linked above and select Fork.
2. Create the fork under your own GitHub account. Do not push changes to the ubern-mialab starter repository.
3. Clone your fork, complete the exercise, then commit and push your work to your fork.
4. Submit both the URL of your fork and the URL or SHA of your final commit through the course submission channel.

If a starter repository displays a 404 page, contact a teaching assistant to request access before forking it.

Getting help

If you encounter issues with the exercises:

• Consult the topics and getting started pages
• Reach out during office hours
• Contact the teaching assistants via email
• Collaborate with your classmates

Remember: these exercises are learning opportunities. Don't hesitate to ask questions!