Using cc3d with multiple channels? about connected-components-3d HOT 11 CLOSED

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hello @william-silversmith ,i want to apply cc3d on segmentation result image containing multiple class and the dimensions of result image is 128128128

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Here's what I suspect you want to do:

# Let multichannel be the segmentation image.

output = np.zeros(multichannel.shape, dtype=np.uint32)
for i in range(multichannel.shape[3]):
   output[:,:,:,i] = cc3d.connected_components(multichannel[:,:,:,i])

If instead by multichannel, you don't mean mean a 4D image and instead mean simply an image with multiple label types (i.e. label 1 might be adjacent to label 2), just use cc3d normally, that's what it was designed for.

from connected-components-3d.

Here's what I suspect you want to do:

# Let multichannel be the segmentation image.

output = np.zeros(multichannel.shape, dtype=np.uint32)
for i in range(multichannel.shape[3]):
   output[:,:,:,i] = cc3d.connected_components(multichannel[:,:,:,i])

If instead by multichannel, you don't mean mean a 4D image and instead mean simply an image with multiple label types (i.e. label 1 might be adjacent to label 2), just use cc3d normally, that's what it was designed for.

Thanks

this is 3d image showing all 3 axis, i want to apply cc3d on it. How will i pass the image to it? i have to convert it into array?

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@william-silversmith

output_dir='./'
PNii  = nibabel.load('./prediction/BraTS20_Training_368/prediction.nii.gz')
P  = PNii.get_fdata()
print(P.shape)
#multichannel='./prediction/BraTS20_Training_368/prediction.nii.gz'
output = np.zeros(P.shape, dtype=np.uint32)
for i in range(P.shape[2]):
   output[:,:,i] = cc3d.connected_components(output[:,:,i])
print(output.shape)
output=sitk.GetImageFromArray(output)
  #get the save path
sitk.WriteImage(output,output_dir + 'new.nii.gz') 

This is my code for apply cc3d and saving it into 3d image with .nii.gz format but the output image is blank image? Please tell me what mistake i am doing here.
Thanks

from connected-components-3d.

Hi sneh, it looks like you are passing a blank output to cc3d. However, the way you're doing it you'll run connected components on each 2D slice, which may not be what you want. The following will probably produce 3D connected components if P is a numpy array.

output_dir='./'
PNii  = nibabel.load('./prediction/BraTS20_Training_368/prediction.nii.gz')
P  = PNii.get_fdata() 
output = cc3d.connected_components(P)
output=sitk.GetImageFromArray(output)
sitk.WriteImage(output,output_dir + 'new.nii.gz') 

from connected-components-3d.

Hi sneh, it looks like you are passing a blank output to cc3d. However, the way you're doing it you'll run connected components on each 2D slice, which may not be what you want. The following will probably produce 3D connected components if P is a numpy array.

output_dir='./'
PNii  = nibabel.load('./prediction/BraTS20_Training_368/prediction.nii.gz')
P  = PNii.get_fdata() 
output = cc3d.connected_components(P)
output=sitk.GetImageFromArray(output)
sitk.WriteImage(output,output_dir + 'new.nii.gz') 

then it gives following error:
TypeError: Type float64 not currently supported.

from connected-components-3d.

If your data is floating point, it's not supported. You'll have to find a way to convert it to integer labels. This could be as easy as P.astype(np.uint64).

from connected-components-3d.

@william-silversmith it worked . thank you. can we increase the intensity value? The image obtained from cc3d is not clear, very difficult to visualize.

from connected-components-3d.

I'm glad it worked! To visualize more easily, try casting the output to a float before passing it to save_images. That functions re-normalizes floats to be more visible.

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Closing this question due to inactivity. Please reopen if you still need help!

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