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Found 3 papers, 3 papers with code
A Robust and Interpretable Deep Learning Framework for Multi-modal Registration via Keypoints
Our core insight which addresses these shortcomings is that corresponding keypoints between images can be used to obtain the optimal transformation via a differentiable closed-form expression.
An Auto-Encoder Strategy for Adaptive Image Segmentation
Thus there is a strong need for deep learning-based segmentation tools that do not require heavy supervision and can continuously adapt.
A Convolutional Autoencoder Approach to Learn Volumetric Shape Representations for Brain Structures
We propose a novel machine learning strategy for studying neuroanatomical shape variation.
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