diff --git a/Modules/Biophotonics/python/iMC/msi/msimanipulations.py b/Modules/Biophotonics/python/iMC/msi/msimanipulations.py
index c32bb28373..1b462f5596 100644
--- a/Modules/Biophotonics/python/iMC/msi/msimanipulations.py
+++ b/Modules/Biophotonics/python/iMC/msi/msimanipulations.py
@@ -1,111 +1,119 @@
 # -*- coding: utf-8 -*-
 """
 Created on Thu Aug 13 13:42:00 2015
 
 @author: wirkert
 """
 
 import logging
 import copy
 import numpy as np
 
 from scipy.interpolate import interp1d
 
 from imgmani import collapse_image
 import imgmani
 from msi import Msi
 
+
 def apply_segmentation(msi, segmentation):
     """ TODO """
     if (isinstance(segmentation, Msi)):
         # expects just an image, but if a Msi is passed it's also ok
         segmentation = segmentation.get_image()
     segmentation = np.squeeze(segmentation)
     mask = (0 == segmentation)
     # mask needs to be expanded to cover all wavlengths
     wholeMask = np.zeros_like(msi.get_image(), dtype="bool")
     # doesn't seem elegant
     for i in range(wholeMask.shape[-1]):
         wholeMask[:, :, i] = mask
 
     msi.set_mask(wholeMask)
+    return msi
 
 
 def calculate_mean_spectrum(msi):
     """ reduce this image to only its mean spectrum.
     If the msi.get_image() is a masked array these values will be ignored when
     calculating the mean spectrum """
     # reshape to collapse all but last dimension (which contains reflectances)
     collapsedImage = collapse_image(msi.get_image())
     msi.set_image(np.mean(collapsedImage, axis=0))
+    # returns the same msi.
+    return msi
 
 
 def interpolate_wavelengths(msi, newWavelengths):
     """ interpolate image data to fit newWavelengths. Current implementation
     performs simple linear interpolation. Neither existing nor new wavelengths
     need to be sorted. """
     interpolator = interp1d(msi.get_wavelengths(), msi.get_image(), assume_sorted=False)
     msi.set_image(interpolator(newWavelengths))
     msi.set_wavelengths(newWavelengths)
+    return msi
 
 
 def normalize_integration_times(msi):
     """ divides by integration times """
     if ('integration times' not in msi.get_properties()):
         logging.warn("warning: trying to normalize integration times for "
             "image without the integration time property")
-        return
+        return msi
 
     original_shape = msi.get_image().shape
     collapsed_image = collapse_image(msi.get_image())
     collapsed_image = collapsed_image / msi.get_properties()['integration times']
     msi.set_image(collapsed_image.reshape(original_shape))
 
     msi.add_property({'integration times':
         np.ones_like(msi.get_properties()['integration times'])})
+    return msi
 
 
 def dark_correction(msi, dark):
     """" subtract dark current from multi spectral image.
 
     The dark msi should either be of the same shape
     as msi or 1xnr_wavelengths (see tests)."""
     msi.set_image(msi.get_image() - dark.get_image())
-
+    return msi
 
 def flatfield_correction(msi, flatfield):
     """ divide by flatfield to remove dependencies on light source form and
     imaging system.
 
     The flatfield msi should either be of the same shape
     as msi or 1xnr_wavelengths (see tests)."""
     # we copy the flatfield to ensure it is unchanged by the normalization
     flatfield_copy = copy.copy(flatfield)
     normalize_integration_times(flatfield_copy)
     normalize_integration_times(msi)
 
     msi.set_image(msi.get_image() / flatfield_copy.get_image())
-
+    return msi
 
 def image_correction(msi, flatfield, dark):
     """ do the usual image correction:
     msi = ((msi - dark) / integration_time) / ((flatfield - dark) / integration_time)
     this function changes only the msi, flatfield and dark image
     are left unchanged.
     """
     # we need a copy of flatfield since otherwise the dark correction
     # changes the flatfield
     dark_correction(msi, dark)
     flatfield_copy = copy.copy(flatfield)
     dark_correction(flatfield_copy, dark)
     flatfield_correction(msi, flatfield_copy)
+    return msi
 
 
 def get_bands(msi, bands):
     """
     TODO SW: document and test
     """
     msi.set_image(imgmani.get_bands(msi.get_image(), bands))
     if msi.get_wavelengths() is not None:
         msi.set_wavelengths(msi.get_wavelengths()[bands])
+    return msi