Medical Image Analysis in Python_468 x 60 copy 2.png

medical.tar.gz

medical

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

## How to anonymize data
When working with patient images, it is necessary to **anonymize** the files. An example of anonymization is when we transfer images to doctors for marking. The easiest way is to anonymize is to use a ready-made function called `remove_private_tags()`.

* We can remove the **meta** tag using the `delattr()`.
* We can change the **image** tag using `data_element().value` and then save the new file.

# How to anonymize data
When working with patient images, it is necessary to **anonymize** the files. An example of anonymization is when we transfer images to doctors for marking. The easiest way is to anonymize is to use a ready-made function called `remove_private_tags()`.

* We can remove the **meta** tag using the `delattr()`.
* We can change the **image** tag using `data_element().value` and then save the new file.

Learn to anonymize data from DICOM images.

__default

Data Anonymization

How to anonymize data