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Found 8 papers, 2 papers with code
An Arbitrary-Modal Fusion Network for Volumetric Cranial Nerves Tract Segmentation
The segmentation of cranial nerves (CNs) tract provides a valuable quantitative tool for the analysis of the morphology and trajectory of individual CNs.
DeepMpMRI: Tensor-decomposition Regularized Learning for Fast and High-Fidelity Multi-Parametric Microstructural MR Imaging
Deep learning has emerged as a promising approach for learning the nonlinear mapping between diffusion-weighted MR images and tissue parameters, which enables automatic and deep understanding of the brain microstructures.
Anatomy-guided fiber trajectory distribution estimation for cranial nerves tractography
Diffusion MRI tractography is an important tool for identifying and analyzing the intracranial course of cranial nerves (CNs).
Modality Exchange Network for Retinogeniculate Visual Pathway Segmentation
Secondly, we propose a cross-fusion module that further enhances the fusion of information between the two modalities.
LESEN: Label-Efficient deep learning for Multi-parametric MRI-based Visual Pathway Segmentation
Recent research has shown the potential of deep learning in multi-parametric MRI-based visual pathway (VP) segmentation.
Bundle-specific Tractogram Distribution Estimation Using Higher-order Streamline Differential Equation
At the global level, the tractography process is simplified as the estimation of bundle-specific tractogram distribution (BTD) coefficients by minimizing the energy optimization model, and is used to characterize the relations between BTD and diffusion tensor vector under the prior guidance by introducing the tractogram bundle information to provide anatomic priors.
Reconstructing the somatotopic organization of the corticospinal tract remains a challenge for modern tractography methods
The corticospinal tract (CST) is a critically important white matter fiber tract in the human brain that enables control of voluntary movements of the body.
DeepRGVP: A Novel Microstructure-Informed Supervised Contrastive Learning Framework for Automated Identification Of The Retinogeniculate Pathway Using dMRI Tractography
The retinogeniculate pathway (RGVP) is responsible for carrying visual information from the retina to the lateral geniculate nucleus.
