Large-scale 3D image registration based on spatial transformers and stacked convolutional autoencoders
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Updated
Dec 6, 2017 - Python
Large-scale 3D image registration based on spatial transformers and stacked convolutional autoencoders
Longitudinal In-vivo Detection of Synapses
Image registration using pytorch
General deep learning-based fast image registration framework for clinical thoracic 4D CT data
An unofficial PyTorch implementation of VoxelMorph- An unsupervised 3D deformable image registration method
Joint Vessel Segmentation and Deformable Registration on Multi-Modal Retinal Images based on Style Transfer
Coin Recognition
Similarity Measure. Re-implementation for PyTorch.
braincellcount: count cells in mouse brains
Official Implementation of Deep Aerial Image Matching using PyTorch
[CVPR2020] Unsupervised Multi-Modal Image Registration via Geometry Preserving Image-to-Image Translation
[MICCAI'18] Joint Learning of Motion Estimation and Segmentation for Cardiac MR Image Sequences
Image registration laboratory for 2D and 3D image data
Code used to create the DeepHistReg submission to the ANHIR challenge.
MSKregPy is a collection of algorithms and a GUI for muscoloskeletal image processing and registration
Software used by the AGH team during the ANHIR challenge.
This code allows to reproduce the results of the paper "Robust Image Reconstruction with Misaligned Structural Information" which aims to reconstruct an image from an indirect measurement whilst registering it with a structural side information from a different modality.
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