diff --git a/make_image_from_bin.py b/make_image_from_bin.py
index 2c438f7..dcd3655 100755
--- a/make_image_from_bin.py
+++ b/make_image_from_bin.py
@@ -82,6 +82,7 @@ def make_image_from_bin( image, binfile, mask ):
     imdat=nim.get_data()
     print "shape",shape(a)
     print "sum",sum(imdat)
+    imdat=imdat.astype('int16')
 
     # map the binary data to mask
     mask_voxels=(imdat.flatten()>0).sum()
@@ -91,6 +92,7 @@ def make_image_from_bin( image, binfile, mask ):
     # write out the image as nifti
     thdr=nim.get_header()
     thdr['scl_slope']=1
+    thdr.set_data_dtype('int16')
     
     nim_aff = nim.get_affine()
 
diff --git a/make_image_from_bin_renum.py b/make_image_from_bin_renum.py
index 3c5f0e9..7a83350 100755
--- a/make_image_from_bin_renum.py
+++ b/make_image_from_bin_renum.py
@@ -89,12 +89,17 @@ def make_image_from_bin_renum( image, binfile, mask ):
         b[a==unique_a[i]]=i+1
 
     imdat=nim.get_data()
+    imdat=imdat.astype('int16')
 
     # map the binary data to mask
     imdat[imdat>0]=1
     imdat[imdat>0]=short(b[0:sum(imdat)].flatten())
 
+    # Get the mask header and change the dtype
+    nim_head = nim.get_header()
+    nim_head.set_data_dtype('int16')
+    
     # write out the image as nifti
-    nim_out = nb.Nifti1Image(imdat, nim.get_affine(), nim.get_header())
+    nim_out = nb.Nifti1Image(imdat, nim.get_affine(), nim_head)
     #nim_out.set_data_dtype('int16')
     nim_out.to_filename(image)
diff --git a/nifti_gen_fix.py b/nifti_gen_fix.py
new file mode 100644
index 0000000..5d11b58
--- /dev/null
+++ b/nifti_gen_fix.py
@@ -0,0 +1,48 @@
+"""
+Temporary band-aid script to generate NIfTI images from NumPY parcellation data.
+
+Written by Dan Lurie (danjlurie@gmail.com).
+
+Usage:
+
+python nifti_gen_fix.py /path/to/parcel_data.npy /path/to/mask.nii.gz /path/to/new_atlas_image.nii.gz
+
+"""
+
+
+import sys
+import numpy as np
+import nibabel as nib
+
+
+
+# Read in command line arguments.
+parcel_path, mask_path, out_path = sys.argv[1:4]
+
+# Load parcellation data.
+parcel_data = np.load(parcel_path)
+
+# Load the mask file.
+mask_file = nib.load(mask_path)
+
+# Get the mask data.
+mask_data = mask_file.get_data()
+
+# Recast the mask data as float 64 to match parcellation data.
+atlas_data = mask_data.astype('float64')
+
+# Copy the parcellation data to the within-mask voxels.
+atlas_data[atlas_data == 1] = parcel_data.ravel()
+
+# Get the affine and header from the mask.
+mask_affine = mask_file.get_affine()
+mask_header = mask_file.get_header()
+
+# Set the data type for the header to float64.
+mask_header.set_data_dtype('float64')
+
+# Create a NIfTI image from the atlas data.
+atlas_image = nib.Nifti1Image(atlas_data, mask_affine, mask_header)
+
+# Write the NIfTI file.
+atlas_image.to_filename(out_path)