[HTML][HTML] Quantitative mapping of the brain's structural connectivity using diffusion MRI tractography: A review
Diffusion magnetic resonance imaging (dMRI) tractography is an advanced imaging
technique that enables in vivo reconstruction of the brain's white matter connections at …
technique that enables in vivo reconstruction of the brain's white matter connections at …
A review of predictive and contrastive self-supervised learning for medical images
WC Wang, E Ahn, D Feng, J Kim - Machine Intelligence Research, 2023 - Springer
Over the last decade, supervised deep learning on manually annotated big data has been
progressing significantly on computer vision tasks. But, the application of deep learning in …
progressing significantly on computer vision tasks. But, the application of deep learning in …
Superficial white matter analysis: An efficient point-cloud-based deep learning framework with supervised contrastive learning for consistent tractography parcellation …
Diffusion MRI tractography is an advanced imaging technique that enables in vivo mapping
of the brain's white matter connections. White matter parcellation classifies tractography …
of the brain's white matter connections. White matter parcellation classifies tractography …
One-shot segmentation of novel white matter tracts via extensive data augmentation and adaptive knowledge transfer
The use of convolutional neural networks (CNNs) has allowed accurate white matter (WM)
tract segmentation on diffusion magnetic resonance imaging (dMRI). To train the CNN …
tract segmentation on diffusion magnetic resonance imaging (dMRI). To train the CNN …
Supwma: consistent and efficient tractography parcellation of superficial white matter with deep learning
White matter parcellation classifies tractography streamlines into clusters or anatomically
meaningful tracts to enable quantification and visualization. Most parcellation methods focus …
meaningful tracts to enable quantification and visualization. Most parcellation methods focus …
[HTML][HTML] FIESTA: Autoencoders for accurate fiber segmentation in tractography
White matter bundle segmentation is a cornerstone of modern tractography to study the
brain's structural connectivity in domains such as neurological disorders, neurosurgery, and …
brain's structural connectivity in domains such as neurological disorders, neurosurgery, and …
[HTML][HTML] Deep fiber clustering: anatomically informed fiber clustering with self-supervised deep learning for fast and effective tractography parcellation
White matter fiber clustering is an important strategy for white matter parcellation, which
enables quantitative analysis of brain connections in health and disease. In combination …
enables quantitative analysis of brain connections in health and disease. In combination …
Computational approaches for the reconstruction of optic nerve fibers along the visual pathway from medical images: a comprehensive review
R Jin, Y Cai, S Zhang, T Yang, H Feng… - Frontiers in …, 2023 - frontiersin.org
Optic never fibers in the visual pathway play significant roles in vision formation. Damages of
optic nerve fibers are biomarkers for the diagnosis of various ophthalmological and …
optic nerve fibers are biomarkers for the diagnosis of various ophthalmological and …
[HTML][HTML] Superficial white matter bundle atlas based on hierarchical fiber clustering over probabilistic tractography data
The study of short association fibers is still an incomplete task due to their higher inter-
subject variability and the smaller size of this kind of fibers in comparison to known long …
subject variability and the smaller size of this kind of fibers in comparison to known long …
TractGeoNet: A geometric deep learning framework for pointwise analysis of tract microstructure to predict language assessment performance
We propose a geometric deep-learning-based framework, TractGeoNet, for performing
regression using diffusion magnetic resonance imaging (dMRI) tractography and associated …
regression using diffusion magnetic resonance imaging (dMRI) tractography and associated …