main.py

from matplotlib import pyplot as plt
from skimage import data
from skimage.feature import blob_dog, blob_log, blob_doh
from math import sqrt
from skimage.color import rgb2gray

image = data.imread('./lung-window.png')[100:400, 100:650]
image_gray = rgb2gray(image)

blobs_log = blob_log(image_gray, max_sigma=30, num_sigma=10, threshold=.1)
# Compute radii in the 3rd column.
blobs_log[:, 2] = blobs_log[:, 2] * sqrt(2)

blobs_dog = blob_dog(image_gray, max_sigma=30, threshold=.1)
blobs_dog[:, 2] = blobs_dog[:, 2] * sqrt(2)

blobs_doh = blob_doh(image_gray, max_sigma=30, threshold=.01)

blobs_list = [blobs_log, blobs_dog, blobs_doh]
colors = ['yellow', 'lime', 'red']
titles = [
    'Laplacian of Gaussian', 'Difference of Gaussian', 'Determinant of Hessian'
]
sequence = zip(blobs_list, colors, titles)

fig, axes = plt.subplots(
    1, 3, sharex=True, sharey=True, subplot_kw={'adjustable': 'box-forced'})
axes = axes.ravel()
for blobs, color, title in sequence:
    ax = axes[0]
    axes = axes[1:]
    ax.set_title(title)
    ax.imshow(image, interpolation='nearest')
    for blob in blobs:
        y, x, r = blob
        c = plt.Circle((x, y), r, color=color, linewidth=2, fill=False)
        ax.add_patch(c)

plt.show()