Feb 13, 2021 · We validate our equivariant method on multiple-sclerosis lesion segmentation. Our proposed neural networks yield better results and require ...
Rotationally and translationally equivariant layers and networks for deep learning on diffusion MRI (dMRI) scans. In this paper we showed that adding rotational ...
A roto-translation of an object in the scanner causes a roto-translation of the image in position space (p-space) and rotation in q-space. We propose a network ...
We propose neural networks equivariant under rotations and translations for diffusion MRI (dMRI) data and therefore generalize prior work to the 6D space of ...
This work generalizes the equivariant method to 6D diffusion MRI data, ensuring joint equivariance under 3D roto-translations in image space and the ...
People also ask
What is rotation equivariance?
How does DWI work in MRI?
Feb 13, 2021 · Such equiv- ariant deep learning is appropriate for diffusion MRI, because microstructural and macrostructural features such as neural fibers ...
Such equivariant deep learning is appropriate for diffusion MRI, because microstructural and macrostructural features such as neural fibers can appear at many ...
Feb 28, 2024 · This work constructs equivariant deep learning layers which respect to symmetries of spatial rotations, reflections, and translations, alongside ...
Apr 4, 2023 · This work constructs equivariant deep learning layers which respect to symmetries of spatial rotations, reflections, and translations, alongside ...
Apr 12, 2023 · This work constructs equivariant deep learning layers which respect to symmetries of spatial rotations, reflections, and translations ...