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# Biomedical Image Analysis in Python

Learn the fundamentals of exploring, manipulating, and measuring biomedical image data.

4 Hours15 Videos54 Exercises

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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.

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1. 1

### Exploration

Free

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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Image data
50 xp
100 xp
100 xp
Plot images
100 xp
N-dimensional images
50 xp
Stack images
100 xp
100 xp
Field of view
50 xp
50 xp
Generate subplots
100 xp
Slice 3D images
100 xp
Plot other views
100 xp
2. 2

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.

3. 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.

4. 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.

### In the following Tracks

#### Image Processing with Python

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Datasets

RSNA Hand RadiographOASIS Brain MeasurementsSunnybrook Cardiac MRITCIA Chest CT (Sample)

Collaborators

Prerequisites

Intermediate Python
Stephen Bailey

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