skill track 03
Image Analysis
Introduction to Image Analysis.
Description
This track covers exploring, manipulating and measuring biomedical image data.
By the end of these notebooks, you should feel more comfortable with:
▸Competence in exploring, manipulating, and analyzing biomedical image data using Python and relevant libraries
▸Proficiency in image processing techniques including segmentation, filtering, and measurement in biomedical contexts
▸Understanding of how to assess and compare biomedical images for disease evaluation and structural analysis
Announcements
In this skill track, the notebooks build on each other. Therefore, complete them in the order given!
Requirements
- ▸You should have understood the basic concepts of Python — otherwise revisit the Introductory notebooks
- ▸Data from open-source databases is loaded automatically at the beginning of each notebook in Google Colab
- ▸Have a look at the theoretical basics before you start with the notebooks
Syllabus
Theoretical Basics
▶View Slide DeckReferences
CT scan: The Cancer Imaging Archive · Hand radiograph: RSNA 2017 Pediatric Bone Age Challenge · MRI: Sunnybrook Cardiac Dataset · Head MRI: Lionheart et al. (2015), Zenodo · OASIS: Marcus et al., J. Cogn. Neurosci. (2007)