DDNet: a novel network for cerebral artery segmentation from MRA IMAGES
Y Zhang, L Chen - 2019 12th International Congress on Image …, 2019 - ieeexplore.ieee.org
Brain vascular segmentation is a very important step in the diagnosis and treatment of brain
diseases. Since manual segmentation of the vascular system of the brain is laborious and …
diseases. Since manual segmentation of the vascular system of the brain is laborious and …
TuNet: End-to-end hierarchical brain tumor segmentation using cascaded networks
Glioma is one of the most common types of brain tumors; it arises in the glial cells in the
human brain and in the spinal cord. In addition to having a high mortality rate, glioma …
human brain and in the spinal cord. In addition to having a high mortality rate, glioma …
End-to-end boundary aware networks for medical image segmentation
A Hatamizadeh, D Terzopoulos… - Machine Learning in …, 2019 - Springer
Fully convolutional neural networks (CNNs) have proven to be effective at representing and
classifying textural information, thus transforming image intensity into output class masks …
classifying textural information, thus transforming image intensity into output class masks …
Review of deep learning approaches for the segmentation of multiple sclerosis lesions on brain MRI
In recent years, there have been multiple works of literature reviewing methods for
automatically segmenting multiple sclerosis (MS) lesions. However, there is no literature …
automatically segmenting multiple sclerosis (MS) lesions. However, there is no literature …
[HTML][HTML] Logistic regression–based model is more efficient than u-net model for reliable whole brain magnetic resonance imaging segmentation
Objectives: Automated whole brain segmentation from magnetic resonance images is of
great interest for the development of clinically relevant volumetric markers for various …
great interest for the development of clinically relevant volumetric markers for various …
Neural segmentation of seeding ROIs (sROIs) for pre-surgical brain tractography
I Avital, I Nelkenbaum, G Tsarfaty… - IEEE transactions on …, 2019 - ieeexplore.ieee.org
White matter tractography mapping is an important tool for neuro-surgical planning and
navigation. It relies on the accurate manual delineation of anatomical seeding ROIs (sROIs) …
navigation. It relies on the accurate manual delineation of anatomical seeding ROIs (sROIs) …
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 …
Unsupervised boundary delineation of spinal neural foramina using a multi-feature and adaptive spectral segmentation
As a common disease in the elderly, neural foramina stenosis (NFS) brings a significantly
negative impact on the quality of life due to its symptoms including pain, disability, fall risk …
negative impact on the quality of life due to its symptoms including pain, disability, fall risk …
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 …
Weaving attention U‐net: A novel hybrid CNN and attention‐based method for organs‐at‐risk segmentation in head and neck CT images
Purpose In radiotherapy planning, manual contouring is labor‐intensive and time‐
consuming. Accurate and robust automated segmentation models improve the efficiency …
consuming. Accurate and robust automated segmentation models improve the efficiency …