MOOSE (Multi-organ objective segmentation) a data-centric AI solution that generates multilabel organ segmentations to facilitate systemic TB whole-person research.The pipeline is based on nn-UNet and has the capability to segment 120 unique tissue classes from a whole-body 18F-FDG PET/CT image.
MOOSE fails when presented with a dynamic PET in the latest version. It works as expected with static 3D images.
MOOSE probably doesn't need to do anything special with the 4D dynamic images, but it should probably still produce the segmented CT output. Additionally, it would be great to have a registration between the CT and the final frame of the PET. Motion correction of the PET could then be performed with FALCON, and mapped back to the CT.
MOOSE fails when presented with a dynamic PET in the latest version. It works as expected with static 3D images.
MOOSE probably doesn't need to do anything special with the 4D dynamic images, but it should probably still produce the segmented CT output. Additionally, it would be great to have a registration between the CT and the final frame of the PET. Motion correction of the PET could then be performed with FALCON, and mapped back to the CT.