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In this course, you’ll learn the basics of medical image analysis using Python. You will learn to display and interpret X-ray and CT scans. This course uses relevant Python libraries and commands on medical images for format conversion, segmentation, and analyzing metadata. You can successfully complete this course with only a basic understanding of Python and no background in medical imaging.

Medical Image Analysis in Python

## Here’s what you’ve learned
We hope you had a good experience learning these concepts using Python. By now, you should be able to do the following:
* Explore medical image formats.
* Load and visualize **DICOM** and **NIfTI-1** data formats.
* Explore the metadata of **DICOM** files.
* Change the format of medical images.
* Anonymize data from **DICOM** images.
* Apply windowing and its attributes.
* Visualize the images before and after windowing.
* Auto-segment medical images.
* Window and scale using the **fast.ai** library.








 

# Here’s what you’ve learned
We hope you had a good experience learning these concepts using Python. By now, you should be able to do the following:
* Explore medical image formats.
* Load and visualize **DICOM** and **NIfTI-1** data formats.
* Explore the metadata of **DICOM** files.
* Change the format of medical images.
* Anonymize data from **DICOM** images.
* Apply windowing and its attributes.
* Visualize the images before and after windowing.
* Auto-segment medical images.
* Window and scale using the **fast.ai** library.








 

Let’s wrap up this course with a final note.

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Wrap Up!

Here’s what you’ve learned