eZIS2Python.py

import os
import numpy as np
import nibabel as nib

import matplotlib.pyplot as plt
from matplotlib.colors import LinearSegmentedColormap
%matplotlib inline  

path1 = os.path.join('folder', 'a.img') #path of file 1
img1 = nib.load(path1)
dataarray1=img1.get_data()

path2 = os.path.join('folder', 'b.img') #path of file 2
img2 = nib.load(path2)
dataarray2=img2.get_data()

diffarray= dataarray1-dataarray2 #計算兩個的差值

## 以下為視覺化
cdict1 = {'red':   ((0.0, 0.0, 1.0),
                   #(0.33, 1.0, 1.0),
                   (0.50, 0.0, 0.0),
                   #(0.67, 1.0, 1.0),
                   (1.0, 0.0, 1.0)),

         'green': ((0.0, 0.0, 1.0),
                   #(0.33, 1.0, 1.0),
                   (0.50, 0.0, 0.0),
                   #(0.67, 1.0, 1.0),
                   (1.0, 0.0, 0.0)),

         'blue':  ((0.0, 0.0, 0.0),
                   #(0.33, 1.0, 1.0),
                   (0.50, 0.0, 0.0),
                   #(0.67, 1.0, 1.0),
                   (1.0, 1.0, 0.0))
        }
blue_red1 = LinearSegmentedColormap('BlueRed1', cdict1)
plt.register_cmap(name='BlueRed1', data=cdict1)

def sagi(array, x):
    fig, ax = plt.subplots(1)
    cmap = plt.get_cmap('BlueRed1')
    im = ax.imshow(array[x,:,:].T, cmap=cmap)    
    cbar= plt.colorbar(im)
    im.set_clim(-4,4)
    plt.title(x)
    plt.gca().invert_xaxis()
    plt.gca().invert_yaxis()
    #return fig

def coro(array, y):
    fig, ax = plt.subplots(1)
    cmap = plt.get_cmap('BlueRed1')
    im = ax.imshow(array[:,y,:].T, cmap=cmap)
    cbar= plt.colorbar(im)
    im.set_clim(-4,4)
    plt.title(y)
    plt.gca().invert_xaxis()
    plt.gca().invert_yaxis()
    #return fig

def axial(array, z):
    fig, ax = plt.subplots(1)
    cmap = plt.get_cmap('BlueRed1')
    im = ax.imshow(array[:,:,z].T, cmap=cmap)
    cbar= plt.colorbar(im)
    im.set_clim(-4,4)
    plt.title(z)
    plt.gca().invert_xaxis()
    plt.gca().invert_yaxis()
    
axial(diffarray[:,:,:,0], 35)