diff --git a/VERSION b/VERSION
index 1e126641c538487d3cf47d9296848e2337e4140d..04547808a83a9caab4f4cfdc5e410fe8e7115b38 100644
--- a/VERSION
+++ b/VERSION
@@ -1 +1 @@
-1.0.2-alpha.2
\ No newline at end of file
+1.0.3-alpha.3
diff --git a/src/toolbox_scs/detectors/__init__.py b/src/toolbox_scs/detectors/__init__.py
index 50e9a129e095fa050633ee22541e93a961b1fa08..793b3167fa62eed82bc3e9933a37f433682fd493 100644
--- a/src/toolbox_scs/detectors/__init__.py
+++ b/src/toolbox_scs/detectors/__init__.py
@@ -6,7 +6,7 @@ from .dssc_data import (
     save_to_file, load_from_file)
 from .dssc_misc import (
     load_dssc_info, load_geom, quickmask_DSSC_ASIC, calc_xgm_frame_indices, 
-    create_xgm_pulsemask, get_xgm_binned, get_xgm_formatted)
+    create_xgm_pulsemask, get_xgm_binned, get_xgm_formatted, load_mask)
 from .dssc_processing import (
     split_frames, bin_data_multipr, sum_trains_multipr,
     sum_trains, bin_data)
diff --git a/src/toolbox_scs/detectors/dssc.py b/src/toolbox_scs/detectors/dssc.py
index 6d5d5c49fd3c1423a080c397155952768705e826..19075c325504bc87d556528c193478afdb862a92 100644
--- a/src/toolbox_scs/detectors/dssc.py
+++ b/src/toolbox_scs/detectors/dssc.py
@@ -9,8 +9,8 @@
     comments: 
         - contributions should comply with pep8 code structure guidelines.
         - Plot routines don't fit into objects since they are rather fluent. 
-          They have been outsourced to dssc_plot.py. Alternatively they could 
-          be accessed as tbdet member functions.
+          They have been outsourced to dssc_plot.py. They can now be accessed
+          as tbdet member functions.
 """
 import os
 import logging
@@ -27,7 +27,7 @@ from .dssc_misc import (load_dssc_info, calc_xgm_frame_indices,
 from .dssc_processing import (bin_data, bin_data_multipr, sum_trains, 
     sum_trains_multipr)
 
-__all__ = ["DSSCBinner", "DSSCImage"]
+__all__ = ["DSSCBinner", "DSSCImager"]
 log = logging.getLogger(__name__)
 
 
@@ -199,17 +199,16 @@ class DSSCBinner:
         return data
 
 
-class DSSCImage:
-    def __init__(self,
-                 distance=1, mask_file=''
-                ):
+class DSSCImager:
+    def __init__(self):
         """
-        (doc to be done)
+        (Placeholder for possible future class handling geometrical properties. 
+        Its main method could be to call the azimuthal integrator).
         """
         #self.distance = distance
-        #self.pxpitchh = 236 # horizontal pitch in microns
-        #self.pxpitchv = 204 # vertical pitch in microns
+        #self.pxpitchh = 236 
+        #self.pxpitchv = 204 
         #self.aspect = self.pxpitchv/self.pxpitchh 
-        #self.geom = self.load_geom()
-        #self.imagemask = self.load_mask(mask_file)
+        #self.geom = None
+        #self.mask = None
         pass
diff --git a/src/toolbox_scs/detectors/dssc_misc.py b/src/toolbox_scs/detectors/dssc_misc.py
index cd7899438c7e1b7498fe22e40d4454c06e91b302..f8caeb064307ad5b3128238b65b88f27345a6cc4 100644
--- a/src/toolbox_scs/detectors/dssc_misc.py
+++ b/src/toolbox_scs/detectors/dssc_misc.py
@@ -182,35 +182,3 @@ def load_mask(fname):
     mask = dssc_mask.astype(float)[..., 0] // 255
     mask[dssc_mask==0] = np.nan
     return mask
-
-
-def substract_dark(self, data, dark, keys=['pumped', 'pumped']):
-        """ 
-        Substract dark image from binned processed images
-        
-        Parameters
-        ----------
-        data: xarray.DataArray
-            processed data
-        dark: xarray.DataArray
-            processed dark run corresponding to data
-        key: str
-            name of the dataset to be accessed
-        """
-        return (data[keys[0]] - dark[keys[1]].values)
-
-
-def normalize_binned_data(self, data, norm, keys=['pumped', 'pumped']):
-        """ 
-        Divide processed images
-        
-        Parameters
-        ----------
-        data: xarray.DataArray
-            processed data
-        dark: xarray.DataArray
-            processed dark run corresponding to data
-        key: str
-            name of the dataset to be accessed
-        """
-        return data[keys[0]] / norm[keys[1]]