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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.
Preprocessing pipeline on Brain MR Images through FSL and ANTs, including registration, skull-stripping, bias field correction, enhancement and segmentation.
This repository contains the code of LiviaNET, a 3D fully convolutional neural network that was employed in our work: "3D fully convolutional networks for subcortical segmentation in MRI: A large-scale study"
This repository contrains source code and the report for the Brain Segmentation challenge. It was the final assignment for the Medical Image Segmentation and Analysis course at the University of Girona for the MAIA programme.