Add option for rounding via a transform

Is your feature request related to a problem? Please describe.

Storing NIfTI images is often not done in the right data type (because it is forgotten). I had the issue multiple times that a label / segmentation image which is supposed to only consist of integer values was stored as float and values had slight rounding errors like containing 0.9999999 instead of 1. When this is loaded with LoadImage(dtype=np.int16), this will get set to 0 instead of 1 since LoadImage does only do a .astype and this will simply cut of the value. This is a very hard to find issue if this happens.

Describe the solution you’d like

• One option could be to add a rounding option to LoadImage.
• We could extend AsDiscrete with a rounding option.
• It could also be added to CastToType
• Another option might be to have a specific LoadLabels or LoadDiscreteImage transform

The first option is closed to the issue I described but the rounding seems a bit “out of place”. It definitely fits to AsDiscrete but for loading label data I would always need to do:

Compose([
    LoadImaged(...),
    AsDiscreted(..., round_to=0),
    CastToTyped(dtype=np.int16),
])

I would be in favor of having an explicit LoadLabels or LoadDiscreteImage transform. This is what I’m already using in my local implementation.

[Spenhouet]

If the original problem is that the datatype is lost when we read in the image, would the simplest solution not be to store the datatype in the dictionary of meta data?

No, the issue is that a NIfTI file is simply stored as float instead of explicitly as integer (human error). For segmentation images we only expect integers. Therefore a

1. Load as float image
2. Round values
3. Cast type to integer

is the savest way to load label / segmentation data.

[wyli]

yes, AsDiscrete could have a rounding method option. thanks for the report, I think we should also update the tutorial to show the usage.