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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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A Method for 6D Pose Estimation of Free-Form Rigid Objects Using Point Pair Features on Range Data

Sensors (Basel, Switzerland), 2018-08, Vol.18 (8), p.2678

2018

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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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Acute ischemic stroke lesion core segmentation in CT perfusion images using fully convolutional neural networks

Computers in biology and medicine, 2019-12, Vol.115, p.103487-103487, Article 103487

2019

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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 Qualitative Review on 3D Coarse Registration Methods

ACM computing surveys, 2015-04, Vol.47 (3), p.1-36

2015

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Objective Evaluation of Multiple Sclerosis Lesion Segmentation using a Data Management and Processing Infrastructure

Scientific reports, 2018-09, Vol.8 (1), p.13650-17, Article 13650

2018

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Deep learning for mass detection in Full Field Digital Mammograms

Computers in biology and medicine, 2020-06, Vol.121, p.103774-103774, Article 103774

2020

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Automatic mass detection in mammograms using deep convolutional neural networks

Journal of medical imaging (Bellingham, Wash.), 2019-07, Vol.6 (3), p.031409-031409

2019

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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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Characterising biofilm development on granular activated carbon used for drinking water production

Water research (Oxford), 2013-03, Vol.47 (3), p.1101-1110

2013

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Acute and sub-acute stroke lesion segmentation from multimodal MRI

Computer methods and programs in biomedicine, 2020-10, Vol.194, p.105521-105521, Article 105521

2020

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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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Review of the dielectric properties of nanofiltration membranes and verification of the single oriented layer approximation

Advances in colloid and interface science, 2012-05, Vol.173, p.1-11

2012

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Comparison of 10 brain tissue segmentation methods using revisited IBSR annotations

Journal of magnetic resonance imaging, 2015-01, Vol.41 (1), p.93-101

2015

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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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Generating Longitudinal Atrophy Evaluation Datasets on Brain Magnetic Resonance Images Using Convolutional Neural Networks and Segmentation Priors

Neuroinformatics (Totowa, N.J.), 2021-07, Vol.19 (3), p.477-492

2021

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Forward Osmosis as Concentration Process: Review of Opportunities and Challenges

Membranes (Basel), 2020-10, Vol.10 (10), p.284

2020

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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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Minimizing the effect of white matter lesions on deep learning based tissue segmentation for brain volumetry

Computerized medical imaging and graphics, 2023-01, Vol.103, p.102157-102157, Article 102157

2023

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Submerged osmotic processes: Design and operation of hollow fiber forward osmosis modules

Desalination, 2021-12, Vol.518, p.115281, Article 115281

2021

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

A Method for 6D Pose Estimation of Free-Form Rigid Objects Using Point Pair Features on Range Data

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

Acute ischemic stroke lesion core segmentation in CT perfusion images using fully convolutional neural networks

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

A Qualitative Review on 3D Coarse Registration Methods

Objective Evaluation of Multiple Sclerosis Lesion Segmentation using a Data Management and Processing Infrastructure

Deep learning for mass detection in Full Field Digital Mammograms

Automatic mass detection in mammograms using deep convolutional neural networks

A review on brain structures segmentation in magnetic resonance imaging

Characterising biofilm development on granular activated carbon used for drinking water production

Acute and sub-acute stroke lesion segmentation from multimodal MRI

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

Review of the dielectric properties of nanofiltration membranes and verification of the single oriented layer approximation

Comparison of 10 brain tissue segmentation methods using revisited IBSR annotations

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

Generating Longitudinal Atrophy Evaluation Datasets on Brain Magnetic Resonance Images Using Convolutional Neural Networks and Segmentation Priors

Forward Osmosis as Concentration Process: Review of Opportunities and Challenges

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

Minimizing the effect of white matter lesions on deep learning based tissue segmentation for brain volumetry

Submerged osmotic processes: Design and operation of hollow fiber forward osmosis modules

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