Topics

Explore the key concepts and techniques covered in the Medical Image Analysis Lab:

Core Topics

Clinical Background

Understanding the medical context and clinical significance of brain tissue segmentation.

Data

Learn about the MR imaging data used in the course and its characteristics.

Pipeline Components

The complete image analysis pipeline consists of several key stages:

• Pre-processing - Image normalization and preparation
• Registration - Aligning images to common reference space
• Feature Extraction - Computing informative features from images
• Voxel-wise Tissue Classification - Machine learning for segmentation
• Post-processing - Refining segmentation results
• Evaluation - Quantitative assessment of performance

Learning Path

These topics are covered progressively throughout the course:

1. Weeks 1-3: Introduction, clinical background, and software tools
2. Weeks 4-5: Pipeline implementation and feature extraction
3. Week 6: Visualization and documentation
4. Weeks 7-14: Project work applying these concepts

For detailed information on each topic, visit the course GitBook.