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Biomedical Image Analysis in Python

IntermediateSkill Level
4.8+
223 reviews
Updated 05/2026
Learn the fundamentals of exploring, manipulating, and measuring biomedical image data.
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PythonData Manipulation4 hr15 videos54 Exercises4,400 XP23,194Statement of Accomplishment

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Course Description

The field of biomedical imaging has exploded in recent years - but for the uninitiated, even loading data can be a challenge! In this introductory course, you'll learn the fundamentals of image analysis using NumPy, SciPy, and Matplotlib. You'll navigate through a whole-body CT scan, segment a cardiac MRI time series, and determine whether Alzheimer’s disease changes brain structure. Even if you have never worked with images before, you will finish the course with a solid toolkit for entering this dynamic field.

Prerequisites

Intermediate Python
1

Exploration

Prepare to conquer the Nth dimension! To begin the course, you'll learn how to load, build and navigate N-dimensional images using a CT image of the human chest. You'll also leverage the useful ImageIO package and hone your NumPy and matplotlib skills.
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2

Masks and Filters

Cut image processing to the bone by transforming x-ray images. You'll learn how to exploit intensity patterns to select sub-regions of an array, and you'll use convolutional filters to detect interesting features. You'll also use SciPy's ndimage module, which contains a treasure trove of image processing tools.
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3

Measurement

In this chapter, you'll get to the heart of image analysis: object measurement. Using a 4D cardiac time series, you'll determine if a patient is likely to have heart disease. Along the way, you'll learn the fundamentals of image segmentation, object labeling, and morphological measurement.
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4

Image Comparison

For the final chapter, you'll need to use your brain... and hundreds of others! Drawing data from more than 400 open-access MR images, you'll learn the basics of registration, resampling, and image comparison. Then, you'll use the extracted measurements to evaluate the effect of Alzheimer's Disease on brain structure.
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Biomedical Image Analysis in Python
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*4.8
from 223 reviews
82%
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  • Blair
    yesterday

  • Dina
    3 days ago

  • dai
    4 days ago

  • Zeyad
    4 days ago

  • Lamis
    4 days ago

  • Mohamed
    4 days ago

    i learned alot thanks

Blair

Dina

dai

FAQs

Do I need prior image analysis experience for this course?

No. This is a beginner-friendly introduction to biomedical image analysis. You only need Intermediate Python and Introduction to Python as prerequisites.

What types of medical images will I analyze?

You work with whole-body CT scans, cardiac MRI time series, and over 400 open-access brain MR images to learn loading, segmentation, measurement, and comparison techniques.

Which Python libraries are used for image processing?

You use NumPy for array manipulation, SciPy's ndimage module for filtering and measurement, Matplotlib for visualization, and ImageIO for loading image data.

What clinical question does the final chapter address?

You investigate whether Alzheimer's disease changes brain structure by comparing measurements from hundreds of MR images using registration, resampling, and image comparison techniques.

How many exercises does this course have?

The course includes 83 exercises across 4 chapters, making it one of the most hands-on courses available. The median completion time is about 4.3 hours.

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