A joint 3d+ 2d fully convolutional framework for subcortical segmentation
In this paper, we proposed and validated a novel joint 3D+ 2D fully convolutional framework
for segmenting subcortical structures from magnetic resonance images (MRIs). A 2D …
for segmenting subcortical structures from magnetic resonance images (MRIs). A 2D …
A multi-atlas guided 3D fully convolutional network for MRI-based subcortical segmentation
In this paper, we proposed and validated an effective multi-atlas guided 3D fully
convolutional network (FCN) for segmenting subcortical structures from magnetic resonance …
convolutional network (FCN) for segmenting subcortical structures from magnetic resonance …
Multi-atlas subcortical segmentation: an orchestration of 3D fully convolutional network and generalized mixture function
J Wu, S He, S Zhou - Machine Vision and Applications, 2023 - Springer
To accurately segment subcortical structures and therefore profit for numerous
neuroimaging applications, we proposed a multi-atlas subcortical segmentation method by …
neuroimaging applications, we proposed a multi-atlas subcortical segmentation method by …
3D fully convolutional networks for subcortical segmentation in MRI: A large-scale study
This study investigates a 3D and fully convolutional neural network (CNN) for subcortical
brain structure segmentation in MRI. 3D CNN architectures have been generally avoided …
brain structure segmentation in MRI. 3D CNN architectures have been generally avoided …
MRI subcortical segmentation in neurodegeneration with cascaded 3D CNNs
The subcortical structures of the brain are relevant for many neurodegenerative diseases
like Huntington's disease (HD). Quantitative segmentation of these structures from magnetic …
like Huntington's disease (HD). Quantitative segmentation of these structures from magnetic …
MSGSE-Net: Multi-scale guided squeeze-and-excitation network for subcortical brain structure segmentation
X Li, Y Wei, L Wang, S Fu, C Wang - Neurocomputing, 2021 - Elsevier
Convolutional neural networks (CNNs) have been achieving remarkable results in medical
image segmentation. However, for accurate segmentation of subcortical brain structure in …
image segmentation. However, for accurate segmentation of subcortical brain structure in …
ψ-net: Stacking densely convolutional lstms for sub-cortical brain structure segmentation
Sub-cortical brain structure segmentation is of great importance for diagnosing
neuropsychiatric disorders. However, developing an automatic approach to segmenting sub …
neuropsychiatric disorders. However, developing an automatic approach to segmenting sub …
Brain segmentation based on multi-atlas and diffeomorphism guided 3D fully convolutional network ensembles
In this study, we proposed and validated a multi-atlas and diffeomorphism guided 3D fully
convolutional network (FCN) ensemble model (M-FCN) for segmenting brain anatomical …
convolutional network (FCN) ensemble model (M-FCN) for segmenting brain anatomical …
TABSurfer: a Hybrid Deep Learning Architecture for Subcortical Segmentation
A Cao, VM Rao, K Liu, X Liu, AF Laine… - arXiv preprint arXiv …, 2023 - arxiv.org
Subcortical segmentation remains challenging despite its important applications in
quantitative structural analysis of brain MRI scans. The most accurate method, manual …
quantitative structural analysis of brain MRI scans. The most accurate method, manual …
[HTML][HTML] Automated sub-cortical brain structure segmentation combining spatial and deep convolutional features
Sub-cortical brain structure segmentation in Magnetic Resonance Images (MRI) has
attracted the interest of the research community for a long time as morphological changes in …
attracted the interest of the research community for a long time as morphological changes in …