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.
The stool has a similar Houndsfield unit to fat. In patients with watery stool, the visceral label segmentation includes the stool. In more constipated patients the differentiation works better.
This finding will affect volumetry-based studies (cachexia). A temporary solution will be to use the L3 approach, where only the relevant label segmentations are considered.
The stool has a similar Houndsfield unit to fat. In patients with watery stool, the visceral label segmentation includes the stool. In more constipated patients the differentiation works better. This finding will affect volumetry-based studies (cachexia). A temporary solution will be to use the L3 approach, where only the relevant label segmentations are considered.