Cntseg: A multimodal deep-learning-based network for cranial nerves tract segmentation
The segmentation of cranial nerves (CNs) tracts based on diffusion magnetic resonance
imaging (dMRI) provides a valuable quantitative tool for the analysis of the morphology and …
imaging (dMRI) provides a valuable quantitative tool for the analysis of the morphology and …
[HTML][HTML] Neuro4Neuro: a neural network approach for neural tract segmentation using large-scale population-based diffusion imaging
Subtle changes in white matter (WM) microstructure have been associated with normal
aging and neurodegeneration. To study these associations in more detail, it is highly …
aging and neurodegeneration. To study these associations in more detail, it is highly …
[HTML][HTML] Automated segmentation of trigeminal nerve and cerebrovasculature in MR-angiography images by deep learning
J Lin, L Mou, Q Yan, S Ma, X Yue, S Zhou… - Frontiers in …, 2021 - frontiersin.org
Trigeminal neuralgia caused by paroxysmal and severe pain in the distribution of the
trigeminal nerve is a rare chronic pain disorder. It is generally accepted that compression of …
trigeminal nerve is a rare chronic pain disorder. It is generally accepted that compression of …
CS-Net: Channel and spatial attention network for curvilinear structure segmentation
The detection of curvilinear structures in medical images, eg, blood vessels or nerve fibers,
is important in aiding management of many diseases. In this work, we propose a general …
is important in aiding management of many diseases. In this work, we propose a general …
White matter tract segmentation with self-supervised learning
Q Lu, Y Li, C Ye - Medical Image Computing and Computer Assisted …, 2020 - Springer
White matter tract segmentation based on diffusion magnetic resonance imaging (dMRI)
plays an important role in brain analysis. Deep learning based methods of white matter tract …
plays an important role in brain analysis. Deep learning based methods of white matter tract …
QuickNAT: A fully convolutional network for quick and accurate segmentation of neuroanatomy
Whole brain segmentation from structural magnetic resonance imaging (MRI) is a
prerequisite for most morphological analyses, but is computationally intense and can …
prerequisite for most morphological analyses, but is computationally intense and can …
[HTML][HTML] RFTNet: Region–Attention Fusion Network Combined with Dual-Branch Vision Transformer for Multimodal Brain Tumor Image Segmentation
C Jiao, T Yang, Y Yan, A Yang - Electronics, 2023 - mdpi.com
Brain tumor image segmentation plays a significant auxiliary role in clinical diagnosis.
Recently, deep learning has been introduced into multimodal segmentation tasks, which …
Recently, deep learning has been introduced into multimodal segmentation tasks, which …
DeepNAT: Deep convolutional neural network for segmenting neuroanatomy
We introduce DeepNAT, a 3D Deep convolutional neural network for the automatic
segmentation of NeuroAnaTomy in T1-weighted magnetic resonance images. DeepNAT is …
segmentation of NeuroAnaTomy in T1-weighted magnetic resonance images. DeepNAT is …
FABnet: feature attention-based network for simultaneous segmentation of microvessels and nerves in routine histology images of oral cancer
Perineural invasion (PNI), lymphovascular invasion (LVI) and tumor angiogenesis have
strong correlation with cancer recurrence, metastasis and poor patient survival. The accurate …
strong correlation with cancer recurrence, metastasis and poor patient survival. The accurate …
[HTML][HTML] O-Net: a novel framework with deep fusion of CNN and transformer for simultaneous segmentation and classification
The application of deep learning in the medical field has continuously made huge
breakthroughs in recent years. Based on convolutional neural network (CNN), the U-Net …
breakthroughs in recent years. Based on convolutional neural network (CNN), the U-Net …