Moving objects cause motion artefacts when their enclosing volume is acquired as a stack of image slices. We present a fast multi-GPU accelerated implementation of slice-to-volume registration based super-resolution reconstruction with automatic outlier rejection and intensity bias correction.
CIMAS is a pipeline for cardiac MR image segmentation. It has been successfully applied to clinical research, segmenting data from the UK Digital Heart project and the UK Biobank project.
OpenMOLE is a workflow engine for executing naturally parallel processes on massively parallel environments. It is free and open-source.
Software which performs whole-brain segmentation of a T1-weighted magnetic resonance brain image. The MALP-EM pipeline includes bias correction, brain extraction, label propagation using multiple atlases, label fusion and finally label refinement using the EM algorithm.
The Developing Brain Region Annotation With Expectation-Maximization software segments neonatal brain MR images into multiple labels.
DeepMedic is our software for brain lesion segmentation based on a multi-scale 3D Deep Convolutional Neural Network coupled with a 3D fully connected Conditional Random Field.
The Medical Image Registration ToolKit provides a collection of libraries and commands to assist in processing and analyzing medical imaging data, including rigid, affine, and deformable registration.
Implementation of Neighbourhood Approximation Forests and Weighted Spectral Distance
Real-time dense visual SLAM system capable of capturing comprehensive dense globally consistent surfel-based maps of room scale environments explored using an RGB-D camera.
Patch-based Evaluation of Image Segmentation
A Python library for patch-based segmentation with spatial context.
Software for medical image registration including rigid, affine and non-rigid registration.