Course Overview

Let’s look at the brief overview of the course.

What does this course cover?

In this course, we will do the following:

  • Get an introduction to medical imaging research.
  • Understand DICOM and NIfTI-1 data formats.
  • Learn to analyze meta tags
  • Convert and anonymize data.
  • Learn about windowing and Hounsfield units and how to apply them
  • Understand the task of image segmentation.
  • Explore third-party libraries for medical image segmentation.
  • Get to know fastai.medical.imaging.

This course will not include deep learning. We’ll focus on the medical imaging formats only.

Who should take this course?

If you’re just getting started with Python, this course probably isn’t for you just yet. The audience for this course is programmers who have a basic working knowledge of Python. This course is not intended for Python beginners.

Required libraries

  • Matplotlib
  • NumPy
  • pandas
  • OpenCV and skimage are optional but helpful.

It is also advisable to have experience with the Linux command line. All examples in this course are written in Python 3.8.