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The effects of task activities and gaming scales on eye reading and visual search performance

Computers in human behavior, 2017-01, Vol.66, p.16-25

2017

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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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A light CNN for detecting COVID-19 from CT scans of the chest

Pattern recognition letters, 2020-12, Vol.140, p.95-100

2020

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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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Man vs. computer: Benchmarking machine learning algorithms for traffic sign recognition

Neural networks, 2012-08, Vol.32, p.323-332

2012

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Combining deep learning and level set for the automated segmentation of the left ventricle of the heart from cardiac cine magnetic resonance

Medical image analysis, 2017-01, Vol.35, p.159-171

2017

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Automatic classification of pulmonary peri-fissural nodules in computed tomography using an ensemble of 2D views and a convolutional neural network out-of-the-box

Medical image analysis, 2015-12, Vol.26 (1), p.195-202

2015

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Multi-site fMRI analysis using privacy-preserving federated learning and domain adaptation: ABIDE results

Medical image analysis, 2020-10, Vol.65, p.101765-101765, Article 101765

2020

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Parallel implementation for 3D medical volume fuzzy segmentation

Pattern recognition letters, 2020-02, Vol.130, p.312-318

2020

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Faster Mean-shift: GPU-accelerated clustering for cosine embedding-based cell segmentation and tracking

Medical image analysis, 2021-07, Vol.71, p.102048-102048, Article 102048

2021

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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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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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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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Automated classification of brain tumor type in whole-slide digital pathology images using local representative tiles

Medical image analysis, 2016-05, Vol.30, p.60-71

2016

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DCAN: Deep contour-aware networks for object instance segmentation from histology images

Medical image analysis, 2017-02, Vol.36, p.135-146

2017

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HBF49 feature set: A first unified baseline for online symbol recognition

Pattern recognition, 2013-01, Vol.46 (1), p.117-130

2013

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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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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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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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A review of 3D/2D registration methods for image-guided interventions

Medical image analysis, 2012-04, Vol.16 (3), p.642-661

2012

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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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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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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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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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Combo loss: Handling input and output imbalance in multi-organ segmentation

Computerized medical imaging and graphics, 2019-07, Vol.75, p.24-33

2019

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The effects of task activities and gaming scales on eye reading and visual search performance

Large scale deep learning for computer aided detection of mammographic lesions

A light CNN for detecting COVID-19 from CT scans of the chest

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

Man vs. computer: Benchmarking machine learning algorithms for traffic sign recognition

Combining deep learning and level set for the automated segmentation of the left ventricle of the heart from cardiac cine magnetic resonance

Automatic classification of pulmonary peri-fissural nodules in computed tomography using an ensemble of 2D views and a convolutional neural network out-of-the-box

Multi-site fMRI analysis using privacy-preserving federated learning and domain adaptation: ABIDE results

Parallel implementation for 3D medical volume fuzzy segmentation

Faster Mean-shift: GPU-accelerated clustering for cosine embedding-based cell segmentation and tracking

Deep learning for chest X-ray analysis: A survey

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

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

Automated classification of brain tumor type in whole-slide digital pathology images using local representative tiles

DCAN: Deep contour-aware networks for object instance segmentation from histology images

HBF49 feature set: A first unified baseline for online symbol recognition

A deep learning framework for unsupervised affine and deformable image registration

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

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

A review of 3D/2D registration methods for image-guided interventions

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

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

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

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

Combo loss: Handling input and output imbalance in multi-organ segmentation

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