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[HTML][HTML] A multi-path 2.5 dimensional convolutional neural network system for segmenting stroke lesions in brain MRI images

Y Xue, FG Farhat, O Boukrina, AM Barrett, JR Binder… - NeuroImage: Clinical, 2020 - Elsevier
Automatic identification of brain lesions from magnetic resonance imaging (MRI) scans of
stroke survivors would be a useful aid in patient diagnosis and treatment planning. It would …
被引用次数：82 相关文章
[PDF] scienceopen.com

[PDF][PDF] A multi-path 2.5 dimensional convolutional neural network system for segmenting stroke lesions in brain MRI images

Y Xue, FG Farhat, O Boukrina, AM Barrett… - NeuroImage …, 2020 - scienceopen.com
Automatic identification of brain lesions from magnetic resonance imaging (MRI) scans of
stroke survivors would be a useful aid in patient diagnosis and treatment planning. It would …

A multi-path 2.5 dimensional convolutional neural network system for segmenting stroke lesions in brain MRI images

Y Xue, FG Farhat, O Boukrina, AM Barrett… - arXiv e …, 2019 - ui.adsabs.harvard.edu
Automatic identification of brain lesions from magnetic resonance imaging (MRI) scans of
stroke survivors would be a useful aid in patient diagnosis and treatment planning. We …
[PDF] rutgers.edu

[PDF][PDF] A multi-path 2.5 dimensional convolutional neural network system for segmenting stroke lesions in brain MRI images

Y Xue, FG Farhat, O Boukrina - NeuroImage …, 2020 - scholarship.libraries.rutgers.edu
Automatic identification of brain lesions from magnetic resonance imaging (MRI) scans of
stroke survivors would be a useful aid in patient diagnosis and treatment planning. It would …

A multi-path 2.5 dimensional convolutional neural network system for segmenting stroke lesions in brain MRI images

Y Xue, FG Farhat, O Boukrina… - NeuroImage …, 2020 - researchwithrutgers.com
Automatic identification of brain lesions from magnetic resonance imaging (MRI) scans of
stroke survivors would be a useful aid in patient diagnosis and treatment planning. It would …
[HTML] nih.gov

[HTML][HTML] A multi-path 2.5 dimensional convolutional neural network system for segmenting stroke lesions in brain MRI images

Y Xue, FG Farhat, O Boukrina, AM Barrett… - NeuroImage …, 2020 - ncbi.nlm.nih.gov
Automatic identification of brain lesions from magnetic resonance imaging (MRI) scans of
stroke survivors would be a useful aid in patient diagnosis and treatment planning. It would …

A multi-path 2.5 dimensional convolutional neural network system for segmenting stroke lesions in brain MRI images

Y Xue, FG Farhat, O Boukrina, AM Barrett… - arXiv preprint arXiv …, 2019 - arxiv.org
Automatic identification of brain lesions from magnetic resonance imaging (MRI) scans of
stroke survivors would be a useful aid in patient diagnosis and treatment planning. We …

A multi-path 2.5 dimensional convolutional neural network system for segmenting stroke lesions in brain MRI images.

Y Xue, FG Farhat, O Boukrina, AM Barrett… - NeuroImage …, 2019 - europepmc.org
Automatic identification of brain lesions from magnetic resonance imaging (MRI) scans of
stroke survivors would be a useful aid in patient diagnosis and treatment planning. It would …
[PDF] researchgate.net

[PDF][PDF] A multi-path 2.5 dimensional convolutional neural network system for segmenting stroke lesions in brain MRI images

Y Xue, FG Farhat, O Boukrina, AM Barrett… - NeuroImage …, 2020 - researchgate.net
Automatic identification of brain lesions from magnetic resonance imaging (MRI) scans of
stroke survivors would be a useful aid in patient diagnosis and treatment planning. It would …

A multi-path 2.5 dimensional convolutional neural network system for segmenting stroke lesions in brain MRI images

Y Xue, FG Farhat, O Boukrina… - NeuroImage …, 2020 - pubmed.ncbi.nlm.nih.gov
Automatic identification of brain lesions from magnetic resonance imaging (MRI) scans of
stroke survivors would be a useful aid in patient diagnosis and treatment planning. It would …