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issue in processing result C2C spine_muscle_adipose_tissue -i dir #128

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ujwalk93 opened this issue May 31, 2024 · 0 comments
Open

issue in processing result C2C spine_muscle_adipose_tissue -i dir #128

ujwalk93 opened this issue May 31, 2024 · 0 comments

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@ujwalk93
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Processing: dir with 529 slices

Inference pipeline:
(1) InferencePipeline
(2) SpineFindDicoms
(3) InferencePipeline
(4) SpineMuscleAdiposeTissueReport

Starting inference pipeline for:

Running InferencePipeline with input keys odict_keys(['inference_pipeline', 'kwargs'])

Inference pipeline:
(1) DicomToNifti
(2) SpineSegmentation
(3) ToCanonical
(4) SpineComputeROIs
(5) SpineMetricsSaver
(6) SpineCoronalSagittalVisualizer
(7) SpineReport

Starting inference pipeline for:

Running DicomToNifti with input keys odict_keys(['inference_pipeline'])
Finished DicomToNifti with output keys dict_keys([])

Running SpineSegmentation with input keys odict_keys(['inference_pipeline'])

If you use this tool please cite: https://pubs.rsna.org/doi/10.1148/ryai.230024

Resampling...
Resampled in 5.60s
Predicting part 1 of 1 ...
100%|███████████████████████████████████████████████████████████████████████████████████| 27/27 [00:11<00:00, 2.45it/s]
Predicted in 90.40s
Resampling...
Finished SpineSegmentation with output keys dict_keys([])

Running ToCanonical with input keys odict_keys(['inference_pipeline'])
Finished ToCanonical with output keys dict_keys([])

Running SpineComputeROIs with input keys odict_keys(['inference_pipeline'])
RuntimeWarning: invalid value encountered in divide
normalized_sums = sums / np.sum(sums)
WARNING:root:Label L5 not found in segmentation volume.
WARNING:root:Label L4 not found in segmentation volume.
WARNING:root:Label L3 not found in segmentation volume.
Computing ROI with centroid 255.000, 198.800, 17.864 and pixel spacing 0.709mm, 0.709mm, 0.625mm...
Elapsed time for erosion operation: 1.412116527557373 seconds
Elapsed time for full ROI computation: 1.7626237869262695 seconds
Computing ROI with centroid 257.000, 196.715, 64.390 and pixel spacing 0.709mm, 0.709mm, 0.625mm...
Killed I have gpu machine in system torch.gpu.is_available() return true
How to handle this situation i need some help here

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