Segment the heart
In this chapter, we'll work with magnetic resonance (MR) imaging data from the Sunnybrook Cardiac Dataset. The full image is a 3D time series spanning a single heartbeat. These data are used by radiologists to measure the ejection fraction: the proportion of blood ejected from the left ventricle during each stroke.
To begin, segment the left ventricle from a single slice of the volume (im). First, you'll filter and mask the image; then you'll label each object with ndi.label().
This chapter's exercises have the following imports:
import imageio
import numpy as np
import scipy.ndimage as ndi
import matplotlib.pyplot as plt
This exercise is part of the course
Biomedical Image Analysis in Python
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Smooth intensity values
im_filt = ____
# Select high-intensity pixels
mask_start = np.where(____, 1, 0)
mask = ____
# Label the objects in "mask"
labels, nlabels = ____
print('Num. Labels:', ____)