Diffeomorphic Medical Image Registration
3개 벤치마크 · 논문 11편 · 이 태스크의 논문 보기 →
Benchmarks
CUMC12
Most implemented
VoxelMorph: A Learning Framework for Deformable Medical Image Registration
Unsupervised Learning of Probabilistic Diffeomorphic Registration for Images and Surfaces
$\texttt{NePhi}$: Neural Deformation Fields for Approximately Diffeomorphic Medical Image Registration
Reliable brain morphometry from contrast‐enhanced T1w‐MRI in patients with multiple sclerosis
Direct cortical thickness estimation using deep learning‐based anatomy segmentation and cortex parcellation
Metric Learning for Image Registration
Papers
A Symmetric Dynamic Learning Framework for Diffeomorphic Medical Image Registration
Diffeomorphic image registration is crucial for various medical imaging applications because it can preserve the topology of the transformation. This study introduces DCCNN-LSTM-Reg, a learning framework that evolves dyn…
Diffeomorphic Medical Image RegistrationImage RegistrationMedical Image Registration$\texttt{NePhi}$: Neural Deformation Fields for Approximately Diffeomorphic Medical Image Registration
This work proposes NePhi, a generalizable neural deformation model which results in approximately diffeomorphic transformations. In contrast to the predominant voxel-based transformation fields used in learning-based reg…
Diffeomorphic Medical Image RegistrationImage RegistrationMedical Image RegistrationReliable brain morphometry from contrast‐enhanced T1w‐MRI in patients with multiple sclerosis
Brain morphometry is usually based on non-enhanced (pre-contrast) T1-weighted MRI. However, such dedicated protocols are sometimes missing in clinical examinations. Instead, an image with a contrast agent is often availa…
3D Medical Imaging SegmentationAnatomyBrain MorphometryBrain Segmentation+3Direct cortical thickness estimation using deep learning‐based anatomy segmentation and cortex parcellation
Accurate and reliable measures of cortical thickness from magnetic resonance imaging are an important biomarker to study neurodegenerative and neurological disorders. Diffeomorphic registration‐based cortical thickness (…
3D Medical Imaging SegmentationAnatomyBrain MorphometryBrain Segmentation+2Metric Learning for Image Registration
Image registration is a key technique in medical image analysis to estimate deformations between image pairs. A good deformation model is important for high-quality estimates. However, most existing approaches use ad-hoc…
Deep LearningDeformable Medical Image RegistrationDiffeomorphic Medical Image RegistrationImage Registration+2Unsupervised Learning of Probabilistic Diffeomorphic Registration for Images and Surfaces
Classical deformable registration techniques achieve impressive results and offer a rigorous theoretical treatment, but are computationally intensive since they solve an optimization problem for each image pair. Recently…
Constrained Diffeomorphic Image RegistrationDeformable Medical Image RegistrationDiffeomorphic Medical Image RegistrationImage Registration+1