In [6]:

    

%matplotlib inline


    

In [7]:

    

from __future__ import division

__author__ = 'Diego'

import os
import nibabel as nib
from scipy import ndimage
import braviz
import numpy as np
import skimage
from skimage import data, filter, color
from skimage.transform import hough_circle
from skimage.feature import peak_local_max
from skimage.draw import circle_perimeter
from skimage.util import img_as_float
import  matplotlib
#matplotlib.use("Qt4Agg")
import matplotlib.pyplot as plt

os.chdir(r"C:\Users\Diego\Documents\prueba_free_surf_400")

skull = nib.load("skull.nii.gz")
data = skull.get_data()
#===============

#data2 = data

data2 = ndimage.median_filter(data,size=3)
#data2 = data2 > 50
slices = np.arange(130,165)

data2 = data2[:,slices,:]

data2 = data2 - np.min(data2)
data2 = data2/np.max(data2)


tot_scores = []


    

In [9]:

    

for s in xrange(data2.shape[1]):
    print s
    ax = plt.gca()
    ax.clear()
    slice = data2[:,s,:].squeeze()
    image = img_as_float(slice)
    edges = filter.canny(image)
    ax.imshow(edges, cmap=plt.cm.gray)
    plt.show()


    

    




0






    













    




1






    













    




2






    













    




3






    













    




4






    













    




5






    













    




6






    













    




7






    













    




8






    













    




9






    













    




10






    













    




11






    













    




12






    













    




13






    













    




14






    













    




15






    













    




16






    













    




17






    













    




18






    













    




19






    













    




20






    













    




21






    













    




22






    













    




23






    













    




24






    













    




25






    













    




26






    













    




27






    













    




28






    













    




29






    













    




30






    













    




31






    













    




32






    













    




33






    













    




34






    

In [ ]: