MultiGPU usage problem

Hi,

I was trying to segment the vertebrae from the CT files with MONAI radiology_full_ct-upgraded-HYBRID and radiology apps with these commands in a multi gpu (8 x NVIDIA T4) environment:

1. monailabel start_server --app apps/radiology --studies apps/datasets/Task09_Spleen/imagesTs --conf models localization_spine,localization_vertebra,segmentation_vertebra

2. monailabel start_server --app apps/radiology_full_ct-upgraded-HYBRID/ --studies datasets/Task09_Spleen/imagesTr --conf models segmentation_full_ct

When I run the first command and activate the MONAILabel plugin from the 3D Slicer on the left side of the screen I was not able to select multiGPU from the list:

First I have tried localization_spine and locate the spine like this:

It is not a good spine localization. How can I make it better? Resampling the input medical images to a lower spacing and retraining the pretrained network will solve the problem? If so, could you please share the pipeline for this case?

For the second step Localization vertebrae I also got the result like this:

Another question is does it matter the input nii.gz file is a colonoscopy CT, chest CT or a CT that is collected to visualize the spine? Maybe the intensity values are changing and this will affect the accuracy of the results? To get better results, do I need to do anything on my CT samples?

The third question is, when I run the vertebra_pipeline the MONAI did not utilize my all 8 GPU and give the error below:

What should I do to get better results and utilize multi-GPUs?

Thanks in advance

Start by reproducing the two monailabel start_server commands with apps/radiology and apps/radiology_full_ct-upgraded-HYBRID, then inspect the vertebra_pipeline entry point and the multi-GPU configuration. Compare the attached localization outputs and GPU error with the app documentation; done means the pipeline behavior, preprocessing expectations, and supported way to use all eight GPUs are documented or corrected.