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Deep convolutional neural networks for brain image analysis on magnetic resonance imaging: a review

Artificial intelligence in medicine, 2019-04, Vol.95, p.64-81

2019

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Automated sub-cortical brain structure segmentation combining spatial and deep convolutional features

Medical image analysis, 2018-08, Vol.48, p.177-186

2018

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A review of atlas-based segmentation for magnetic resonance brain images

Computer methods and programs in biomedicine, 2011-12, Vol.104 (3), p.e158-e177

2011

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A review on brain structures segmentation in magnetic resonance imaging

Artificial intelligence in medicine, 2016-10, Vol.73, p.45-69

2016

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One-shot domain adaptation in multiple sclerosis lesion segmentation using convolutional neural networks

NeuroImage clinical, 2019-01, Vol.21, p.101638-101638, Article 101638

2019

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Segmentation of multiple sclerosis lesions in brain MRI: A review of automated approaches

Information sciences, 2012-03, Vol.186 (1), p.164-185

2012

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A survey of prostate segmentation methodologies in ultrasound, magnetic resonance and computed tomography images

Computer methods and programs in biomedicine, 2012-10, Vol.108 (1), p.262-287

2012

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Improving the detection of new lesions in multiple sclerosis with a cascaded 3D fully convolutional neural network approach

Frontiers in neuroscience, 2022-11, Vol.16, p.1007619-1007619

2022

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A fully convolutional neural network for new T2-w lesion detection in multiple sclerosis

NeuroImage clinical, 2020-01, Vol.25, p.102149-102149, Article 102149

2020

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A white matter lesion-filling approach to improve brain tissue volume measurements

NeuroImage clinical, 2014-01, Vol.6 (C), p.86-92

2014

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Automated tissue segmentation of MR brain images in the presence of white matter lesions

Medical image analysis, 2017-01, Vol.35, p.446-457

2017

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An End-to-End Deep Learning Framework for Predicting Hematoma Expansion in Hemorrhagic Stroke Patients from CT Images

Applied sciences, 2024-04, Vol.14 (7), p.2708

2024

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Multiple Sclerosis Lesion Synthesis in MRI Using an Encoder-Decoder U-NET

IEEE access, 2019, Vol.7, p.25171-25184

2019

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A supervised framework with intensity subtraction and deformation field features for the detection of new T2-w lesions in multiple sclerosis

NeuroImage clinical, 2018-01, Vol.17, p.607-615

2018

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Evaluating the use of synthetic T1-w images in new T2 lesion detection in multiple sclerosis

Frontiers in neuroscience, 2022-09, Vol.16, p.954662

2022

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Quantitative Analysis of Patch-Based Fully Convolutional Neural Networks for Tissue Segmentation on Brain Magnetic Resonance Imaging

IEEE access, 2019, Vol.7, p.89986-90002

2019

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Transductive Transfer Learning for Domain Adaptation in Brain Magnetic Resonance Image Segmentation

Frontiers in neuroscience, 2021-04, Vol.15, p.608808-608808

2021

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Brain structure segmentation in the presence of multiple sclerosis lesions

NeuroImage clinical, 2019-01, Vol.22, p.101709-101709, Article 101709

2019

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Usefulness of Collaborative Work in the Evaluation of Prostate Cancer from MRI

Clinics and practice, 2022-05, Vol.12 (3), p.350-362

2022

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Automated Detection of Lupus White Matter Lesions in MRI

Frontiers in neuroinformatics, 2016-08, Vol.10, p.33-33

2016

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Deciphering multiple sclerosis disability with deep learning attention maps on clinical MRI

NeuroImage clinical, 2023-01, Vol.38, p.103376-103376, Article 103376

2023

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A fully automated pipeline for brain structure segmentation in multiple sclerosis

NeuroImage clinical, 2020-01, Vol.27, p.102306-102306, Article 102306

2020

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Strategies to combine 3D vasculature and brain CTA with deep neural networks: Application to LVO

iScience, 2024-02, Vol.27 (2), p.108881-108881, Article 108881

2024

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Evaluating the effect of multiple sclerosis lesions on automatic brain structure segmentation

NeuroImage clinical, 2017-01, Vol.15, p.228-238

2017

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A Review on Automatic Mammographic Density and Parenchymal Segmentation

International Journal of Breast Cancer, 2015-01, Vol.2015, p.276217-31

2015

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Deep convolutional neural networks for brain image analysis on magnetic resonance imaging: a review

Automated sub-cortical brain structure segmentation combining spatial and deep convolutional features

A review of atlas-based segmentation for magnetic resonance brain images

A review on brain structures segmentation in magnetic resonance imaging

One-shot domain adaptation in multiple sclerosis lesion segmentation using convolutional neural networks

Segmentation of multiple sclerosis lesions in brain MRI: A review of automated approaches

A survey of prostate segmentation methodologies in ultrasound, magnetic resonance and computed tomography images

Improving the detection of new lesions in multiple sclerosis with a cascaded 3D fully convolutional neural network approach

A fully convolutional neural network for new T2-w lesion detection in multiple sclerosis

A white matter lesion-filling approach to improve brain tissue volume measurements

Automated tissue segmentation of MR brain images in the presence of white matter lesions

An End-to-End Deep Learning Framework for Predicting Hematoma Expansion in Hemorrhagic Stroke Patients from CT Images

Multiple Sclerosis Lesion Synthesis in MRI Using an Encoder-Decoder U-NET

A supervised framework with intensity subtraction and deformation field features for the detection of new T2-w lesions in multiple sclerosis

Evaluating the use of synthetic T1-w images in new T2 lesion detection in multiple sclerosis

Quantitative Analysis of Patch-Based Fully Convolutional Neural Networks for Tissue Segmentation on Brain Magnetic Resonance Imaging

Transductive Transfer Learning for Domain Adaptation in Brain Magnetic Resonance Image Segmentation

Brain structure segmentation in the presence of multiple sclerosis lesions

Usefulness of Collaborative Work in the Evaluation of Prostate Cancer from MRI

Automated Detection of Lupus White Matter Lesions in MRI

Deciphering multiple sclerosis disability with deep learning attention maps on clinical MRI

A fully automated pipeline for brain structure segmentation in multiple sclerosis

Strategies to combine 3D vasculature and brain CTA with deep neural networks: Application to LVO

Evaluating the effect of multiple sclerosis lesions on automatic brain structure segmentation

A Review on Automatic Mammographic Density and Parenchymal Segmentation

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