Course Introduction

Overview

Questions

• How can I use this course to be better at my research?

Objectives

• Explain how to get the most from the course
• Demonstrate and explain how the course will be laid out

This is a lesson created in the style of The Carpentries. It is written with the assumption that you already possess skills in terms of git, Python and basic image processing.

The interpretation of medical images for clinical purposes requires skills that take highly trained professionals such as nuclear medicine specialists and radiologists many years to master. This course does not aim to improve such interpretive skills, but rather to enhance the computational skills needed to answer research questions involving medical images.

Some examples of the kinds of research questions that can be answered are:

• Can we predict from brain MRIs when patients will become demented before they do?

• Can we build machine learning models on ultrasound data which can aid in the detection of neuromuscular diseases?

• Are there observable anatomical differences in the brains of autistic people at a population level?

• Can we use existing medical imaging to screen for underdiagnosed conditions like osteoporosis?

You are in all likelihood here because you have a research question which can be answered with the processing and analysis of medical images. This course is meant to aid you.

Note that all figures and data presented are licensed under open-source terms.

Challenge: Can You Do It?

What is the way to use the challenges and question?

Show me the solution

Do not peek, try to solve it yourself. The effort will pay off.