5 results for “topic:ct-segmentation”
[MICCAI 2023] MedNeXt is a fully ConvNeXt architecture for 3D medical image segmentation.
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.
Brain CT image segmentation, normalisation, skull-stripping and total brain/intracranial volume computation.
This is the official repository for Fast-nnUNet, a new fast model inference framework based on the nnUNet framework implementation.
The implementation of our MICCAI22 paper "Asymmetry Disentanglement Network for Interpretable Acute Ischemic Stroke Infarct Segmentation in Non-Contrast CT Scans".