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Calculate distance

A distance transformation calculates the distance from each pixel to a given point, usually the nearest background pixel. This allows you to determine which points in the object are more interior and which are closer to edges.

For this exercise, use the Euclidian distance transform on the left ventricle object in labels.

Este ejercicio forma parte del curso

Biomedical Image Analysis in Python

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Instrucciones del ejercicio

  • Create a mask of left ventricle pixels (Value of 1 in labels).
  • Calculate the distance to background for each pixel using ndi.distance_transform_edt(). Supply pixel dimensions to the sampling argument.
  • Print out the maximum distance and its coordinates using ndi.maximum and ndi.maximum_position.
  • Overlay a slice of the distance map on the original image. This has been done for you.

Ejercicio interactivo práctico

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# Calculate left ventricle distances
lv = np.where(____, 1, 0)
dists = ____

# Report on distances
print('Max distance (mm):', ____)
print('Max location:', ____)

# Plot overlay of distances
overlay = np.where(dists[5] > 0, dists[5], np.nan) 
plt.imshow(overlay, cmap='hot')
format_and_render_plot()
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