Cell detection

cell.py

from skimage import io, filter, morphology, segmentation, measure, img_as_float

import os

# Download the image

if not os.path.exists('cell.png'):
    print "Downloading snowflakes image..."
    import urllib2
    u = urllib2.urlopen('http://people.sc.fsu.edu/~jburkardt/data/tif/cell.png')
    f = open('cell.png', 'w')
    f.write(u.read())
    f.close()

# Load image from disk
image = img_as_float(io.imread('cell.png'))

# Perform edge detection
edges = filter.sobel(image)

# Threshold
image_bw = edges > filter.threshold_otsu(edges)

# Perform morphological opening to join parts together
image_bw = morphology.closing(image_bw, selem=morphology.diamond(3))

# Remove objects touching the image border
image_bw = segmentation.clear_border(image_bw)

# Find individual objects in the image
labels = morphology.label(image_bw, neighbors=8, background=0)

# Mark the cell boundaries
for i in range(labels.max() + 1):
    c = measure.find_contours(labels == i, 0)[0].astype(int)
    image[c[:, 0], c[:, 1]] = 1

io.imshow(image)
io.show()