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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

# Download the datasets
First, create an account on [Kaggle](https://www.kaggle.com/) if you don’t have one already. Then, download the dataset of `stage_2_images` from [here](https://www.kaggle.com/c/siim-acr-pneumothorax-segmentation/data). Open Google Colab from [here](https://colab.research.google.com/).


# Upload onto Google Drive
Follow the steps below to upload the dataset of `stage_2_images`  onto Google Drive:
1. After downloading the `stage_2_images` dataset, unzip it.
2. Access  your Google Drive from the sidebar of the Google Colab.
3. Upload the `stage_2_images` folder onto Google Colab, or upload it onto your Google Drive.

# How to run code to make a histogram
Follow these steps to run code:

1. Create a new notebook by clicking on **“File”** in the menu bar.

2. Install the `pydicom` library using the command below:





 

Learn to download datasets and run a few code examples.

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Appendix

Download the datasets

Upload onto Google Drive

How to run code to make a histogram