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Quantitative analysis of molecular surface based on improved Marching Tetrahedra algorithm

Journal of molecular graphics & modelling, 2012-09, Vol.38, p.314-323

2012

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Medical image processing on the GPU – Past, present and future

Medical image analysis, 2013-12, Vol.17 (8), p.1073-1094

2013

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CLIJ: GPU-accelerated image processing for everyone

Nature methods, 2020-01, Vol.17 (1), p.5

2020

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GPU-accelerated molecular modeling coming of age

Journal of molecular graphics & modelling, 2010-09, Vol.29 (2), p.116-125

2010

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Application of eye tracking in medicine: A survey, research issues and challenges

Computerized medical imaging and graphics, 2018-04, Vol.65, p.176-190

2018

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CHAOS Challenge - combined (CT-MR) healthy abdominal organ segmentation

Medical image analysis, 2021-04, Vol.69, p.101950-101950, Article 101950

2021

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Attention gated networks: Learning to leverage salient regions in medical images

Medical image analysis, 2019-04, Vol.53, p.197-207

2019

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Validation, comparison, and combination of algorithms for automatic detection of pulmonary nodules in computed tomography images: The LUNA16 challenge

Medical image analysis, 2017-12, Vol.42, p.1-13

2017

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A deep learning framework for unsupervised affine and deformable image registration

Medical image analysis, 2019-02, Vol.52, p.128-143

2019

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Deep learning for chest X-ray analysis: A survey

Medical image analysis, 2021-08, Vol.72, p.102125-102125, Article 102125

2021

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Large scale deep learning for computer aided detection of mammographic lesions

Medical image analysis, 2017-01, Vol.35, p.303-312

2017

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Convolutional neural networks for classification of Alzheimer's disease: Overview and reproducible evaluation

Medical image analysis, 2020-07, Vol.63, p.101694-101694, Article 101694

2020

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Embracing imperfect datasets: A review of deep learning solutions for medical image segmentation

Medical image analysis, 2020-07, Vol.63, p.101693-101693, Article 101693

2020

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A survey on active learning and human-in-the-loop deep learning for medical image analysis

Medical image analysis, 2021-07, Vol.71, p.102062-102062, Article 102062

2021

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Image analysis and machine learning in digital pathology: Challenges and opportunities

Medical image analysis, 2016-10, Vol.33, p.170-175

2016

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Evaluation of algorithms for Multi-Modality Whole Heart Segmentation: An open-access grand challenge

Medical image analysis, 2019-12, Vol.58, p.101537-101537, Article 101537

2019

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Central focused convolutional neural networks: Developing a data-driven model for lung nodule segmentation

Medical image analysis, 2017-08, Vol.40, p.172-183

2017

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Disease prediction using graph convolutional networks: Application to Autism Spectrum Disorder and Alzheimer’s disease

Medical image analysis, 2018-08, Vol.48, p.117-130

2018

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Machine learning approaches in medical image analysis: From detection to diagnosis

Medical image analysis, 2016-10, Vol.33, p.94-97

de Bruijne, Marleen

2016

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Self-supervised learning for medical image analysis using image context restoration

Medical image analysis, 2019-12, Vol.58, p.101539-101539, Article 101539

2019

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3D deeply supervised network for automated segmentation of volumetric medical images

Medical image analysis, 2017-10, Vol.41, p.40-54

2017

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Autoencoders for unsupervised anomaly segmentation in brain MR images: A comparative study

Medical image analysis, 2021-04, Vol.69, p.101952-101952, Article 101952

2021

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BIRNet: Brain image registration using dual-supervised fully convolutional networks

Medical image analysis, 2019-05, Vol.54, p.193-206

2019

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A combined deep-learning and deformable-model approach to fully automatic segmentation of the left ventricle in cardiac MRI

Medical image analysis, 2016-05, Vol.30, p.108-119

2016

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Weakly-supervised convolutional neural networks for multimodal image registration

Medical image analysis, 2018-10, Vol.49, p.1-13

2018

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Quantitative analysis of molecular surface based on improved Marching Tetrahedra algorithm

Medical image processing on the GPU – Past, present and future

CLIJ: GPU-accelerated image processing for everyone

GPU-accelerated molecular modeling coming of age

Application of eye tracking in medicine: A survey, research issues and challenges

CHAOS Challenge - combined (CT-MR) healthy abdominal organ segmentation

Attention gated networks: Learning to leverage salient regions in medical images

Validation, comparison, and combination of algorithms for automatic detection of pulmonary nodules in computed tomography images: The LUNA16 challenge

A deep learning framework for unsupervised affine and deformable image registration

Deep learning for chest X-ray analysis: A survey

Large scale deep learning for computer aided detection of mammographic lesions

Convolutional neural networks for classification of Alzheimer's disease: Overview and reproducible evaluation

Embracing imperfect datasets: A review of deep learning solutions for medical image segmentation

A survey on active learning and human-in-the-loop deep learning for medical image analysis

Image analysis and machine learning in digital pathology: Challenges and opportunities

Evaluation of algorithms for Multi-Modality Whole Heart Segmentation: An open-access grand challenge

Central focused convolutional neural networks: Developing a data-driven model for lung nodule segmentation

Disease prediction using graph convolutional networks: Application to Autism Spectrum Disorder and Alzheimer’s disease

Machine learning approaches in medical image analysis: From detection to diagnosis

Self-supervised learning for medical image analysis using image context restoration

3D deeply supervised network for automated segmentation of volumetric medical images

Autoencoders for unsupervised anomaly segmentation in brain MR images: A comparative study

BIRNet: Brain image registration using dual-supervised fully convolutional networks

A combined deep-learning and deformable-model approach to fully automatic segmentation of the left ventricle in cardiac MRI

Weakly-supervised convolutional neural networks for multimodal image registration

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