Pixel type error when using MergeLabelMapFilter


I am running into an error when trying to merge several label maps/masks into one label map. The basics of my code are:

import SimpleITK as sitk

map_files = ['label_map1.nrrd', 'label_map2.nrrd']
map_imgs = [sitk.ReadImage(map) for map in map_files]

combiner = sitk.MergeLabelMapFilter()

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/home/hunglab/mwarkent/.virtualenvs/torch/lib64/python3.6/site-packages/SimpleITK/SimpleITK.py", line 49075, in Execute
    return _SimpleITK.MergeLabelMapFilter_Execute(self, *args)
RuntimeError: Exception thrown in SimpleITK MergeLabelMapFilter_Execute: /tmp/SimpleITK/Code/Common/include/sitkMemberFunctionFactory.hxx:196:
sitk::ERROR: Pixel type: 16-bit unsigned integer is not supported in 3D byN3itk6simple19MergeLabelMapFilterE

I have tried forcing different pixel types when reading in the image with sitk.ReadImage() but the exception is thrown every time. Any idea what the issue is?

So it seems like I needed to convert the segmentation masks into label map objects via sitk.BinaryImageToLabelMap() and then it worked. Maybe Iā€™m using the terms segmentation mask and label map too interchangeably. Could someone clarify the salient differences?

Following from the above code, this fixes it:

label_maps = [sitk.BinaryImageToLabelMap(img) for img in map_imgs]
combined = combiner.Execute(*lmaps)
combined_img = sitk.LabelMapToLabel(combined)

LabelMap is a special data structure, whereas mask image is an image (with binary or enumerated label values).

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There is also ā€œLabelImageToLabelMapFilterā€ which will preserve the label values. Also you can use sitk.Cast(img, sitk.sitkLabelUInt16) to run this filter too.

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There is also ā€œLabelImageToLabelMapFilterā€ which will preserve the label values

@blowekamp Do you mean in place of BinaryImageToLabelMap? If, for example, each image had a sequentially numbered label instead of binary label?


BinaryImageToLabelMap splits the label into distinctly labeled connected components or objects. This does a one to many relabeling.

LabelImageToLabelMap preserved the values/labels of the input image.

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