LoadImaged for 2D/3D grayscale tiff files

Using LoadImaged on a 2D grayscale tiff file with WSIReader and backend=cucim returns an array with 3 “color” channels, which are all identical.

For example,

data_dict = {"image": "test.tif"}
x = np.random.randint(low=0,high=256,size=(128,128),dtype=np.uint8)
io.imsave(data_dict["image"],x) 

print("cucim: shape = " + str(cucim.CuImage(data_dict["image"]).shape))
transform = LoadImaged(keys=["image"], reader=WSIReader, backend='cuCIM')
print("LoadImaged-cucim: shape = " + str(transform(data_dict)["image"].shape))

returns,

cucim: shape = [128, 128, 1]
LoadImaged-cucim: shape = (3, 128, 128)

When using backend=tifffile the files are misread entirely

print("tifffule: shape = " + str(tifffile.imread(data_dict["image"]).shape))
transform = LoadImaged(keys=["image"], reader=WSIReader, backend='tifffile')
print("LoadImaged-tifffile: shape = " + str(transform(data_dict)["image"].shape))

returns,

tifffule: shape = (128, 128)
LoadImaged-tifffile: shape = (3, 128)

Is this the expected behavior? Is there a better way to read 2D grayscale tiff files into monai? How about 3D grayscale tiffs?

Thanks, David

[drbeh]

perhaps in the wsireader it’s useful to raise a runtime error when the input doesn’t have the required colour channels?

@wyli, that depends on the backends and each of them handles this differently, so we don’t know it before loading the image. It should be addressed in cuCIM, so I made an issue on their repo.

[drbeh]

@drbeh , you’re right, my application is not whole slide imaging. I work with microCT data, at a user-facility for scientific applications: https://als.lbl.gov/beamlines/8-3-2/. We don’t use medical imaging formats like dicom. Instead we store raw data in hdf5, but typically give users reconstructions in tiffs (either 3D tiffs or individual 2D slices). Would very much appreciate general tiff support in monai.

@perlmutter, I believe we already support functionality via ITK. You should be able to use ITKReader for your use case. For your example above you can change it to:

import numpy as np                                                                                                                                                                                                                           
from skimage import io
from monai.transforms import LoadImaged
from monai.data.image_reader import ITKReader       

data_dict = {"image": "test.tif"}
x = np.random.randint(low=0,high=256,size=(128,128),dtype=np.uint8)
io.imsave(data_dict["image"],x) 

transformD = LoadImaged(keys=["image"], reader=ITKReader)
image = transformD(data_dict)["image"]
print(f"ITKReader: image shape = {image.shape}")

ITKReader: image shape = (128, 128)