Orthoslicer in Python

function.py

def orthoslicer(stack, direction, coordinates, verbose=False):
    '''Works like "orthogonal view" (CTRL+Shift+H in ImageJ'''
    if verbose:
        print('The input stack has a size of %s x %s x %s px' % (stack.shape[0],
                                                                 stack.shape[1],
                                                                 stack.shape[2]))
        print('Extracting a slice centered %s, %s, %s px in direction %s' % (coordinates[0],
                                                                             coordinates[1],
                                                                             coordinates[2],
                                                                             direction))
    if direction == 0:       
        if verbose:
            print('Extracting YZ slice %s of %s' % (coordinates[0], stack.shape[2]))
        extractedslice = dask.array.rot90(stack[:, :, coordinates[0]])
    elif direction == 1:
        if verbose:
            print('Extracting XZ slice %s of %s' % (coordinates[1], stack.shape[1]))
        extractedslice = stack[:,coordinates[1],:]
    elif direction == 2:
        if verbose:
            print('Extracting slice %s of %s' % (coordinates[2], stack.shape[0]))
        extractedslice = stack[coordinates[2],:,:]
    if verbose:
        plt.figure(999)        
        for anatomical_direction in range(3):
            if anatomical_direction == 0:
                plt.subplot(2,2,2)
                # Flip and rotate the extracted YZ slice, to be exactly consistent with the OrthoViewer of ImageJ
                plt.imshow(skimage.exposure.equalize_adapthist(dask.array.flipud(dask.array.rot90(stack[:, :, coordinates[0]]))))
                plt.axhline(coordinates[1], c=seaborn.color_palette(n_colors=3)[1])
                plt.axvline(coordinates[2], c=seaborn.color_palette(n_colors=3)[2])
                plt.title('YZ slice %s (dir=%s)\nCoords: %s' % (coordinates[0], anatomical_direction, coordinates), color=seaborn.color_palette(n_colors=3)[anatomical_direction])
                plt.gca().tick_params(axis='both', color=seaborn.color_palette(n_colors=3)[anatomical_direction])
            elif anatomical_direction == 1:
                plt.subplot(2,2,3)
                plt.imshow(skimage.exposure.equalize_adapthist(stack[:,coordinates[1],:]))            
                plt.axhline(coordinates[2], c=seaborn.color_palette(n_colors=3)[2])
                plt.axvline(coordinates[0], c=seaborn.color_palette(n_colors=3)[0])
                plt.title('XZ slice %s (dir=%s)\nCoords: %s' % (coordinates[1], anatomical_direction, coordinates), color=seaborn.color_palette(n_colors=3)[anatomical_direction])                
                plt.gca().tick_params(axis='both', color=seaborn.color_palette(n_colors=3)[anatomical_direction])                
            elif anatomical_direction == 2:
                plt.subplot(2,2,1)
                plt.imshow(skimage.exposure.equalize_adapthist(stack[coordinates[2],:,:]))
                plt.axhline(coordinates[1], c=seaborn.color_palette(n_colors=3)[1])
                plt.axvline(coordinates[0], c=seaborn.color_palette(n_colors=3)[0])       
                plt.title('Slice %s (dir=%s)\nCoords: %s' % (coordinates[2], anatomical_direction, coordinates), color=seaborn.color_palette(n_colors=3)[anatomical_direction])
                plt.gca().tick_params(axis='both', color=seaborn.color_palette(n_colors=3)[anatomical_direction])
        plt.tight_layout(pad=0.1)
        plt.show()
    return(extractedslice)

test.py

# Test extraction script
# Coordinates are set at the border of left big blood vessel on slice 2434 on 11um stack of d152, as shown in OrthoViewer of ImageJ
extracted_slice = orthoslicer(Reconstructions[15],
                                            2,
                                            (1296,1784,2600),
                                            verbose=True)
plt.figure()
plt.imshow(extracted_slice)
plt.show()

My code on the left, screenshot of ImageJ on the right.