Bram van Ginneken

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Radboudumc

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Iterative augmentation of visual evidence for weakly-supervised lesion localization in deep interpretability frameworks

Interpretability of deep learning (DL) systems is gaining attention in m...
10/16/2019 ∙ by Cristina González-Gonzalo, et al. ∙ 22 ∙ share

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Contextual Two-Stage U-Nets for Robust Pulmonary Lobe Segmentation in CT Scans of COVID-19 and COPD Patients

Pulmonary lobe segmentation in computed tomography scans is essential fo...
04/16/2020 ∙ by Weiyi Xie, et al. ∙ 17 ∙ share

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BIAS: Transparent reporting of biomedical image analysis challenges

The number of biomedical image analysis challenges organized per year is...
10/09/2019 ∙ by Lena Maier-Hein, et al. ∙ 12 ∙ share

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Is the winner really the best? A critical analysis of common research practice in biomedical image analysis competitions

International challenges have become the standard for validation of biom...
06/06/2018 ∙ by Lena Maier-Hein, et al. ∙ 10 ∙ share

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iW-Net: an automatic and minimalistic interactive lung nodule segmentation deep network

We propose iW-Net, a deep learning model that allows for both automatic ...
11/30/2018 ∙ by Guilherme Aresta, et al. ∙ 8 ∙ share

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The Liver Tumor Segmentation Benchmark (LiTS)

In this work, we report the set-up and results of the Liver Tumor Segmen...
01/13/2019 ∙ by Patrick Bilic, et al. ∙ 8 ∙ share

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Streaming convolutional neural networks for end-to-end learning with multi-megapixel images

Due to memory constraints on current hardware, most convolution neural n...
11/11/2019 ∙ by Hans Pinckaers, et al. ∙ 7 ∙ share

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A deep learning model for segmentation of geographic atrophy to study its long-term natural history

Purpose: To develop and validate a deep learning model for automatic seg...
08/15/2019 ∙ by Bart Liefers, et al. ∙ 5 ∙ share

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Automated Gleason Grading of Prostate Biopsies using Deep Learning

The Gleason score is the most important prognostic marker for prostate c...
07/18/2019 ∙ by Wouter Bulten, et al. ∙ 2 ∙ share

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Automatic calcium scoring in low-dose chest CT using deep neural networks with dilated convolutions

Heavy smokers undergoing screening with low-dose chest CT are affected b...
11/01/2017 ∙ by Nikolas Lessmann, et al. ∙ 0 ∙ share

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Context-aware stacked convolutional neural networks for classification of breast carcinomas in whole-slide histopathology images

Automated classification of histopathological whole-slide images (WSI) o...
05/10/2017 ∙ by Babak Ehteshami Bejnordi, et al. ∙ 0 ∙ share

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Comparison of Different Methods for Tissue Segmentation in Histopathological Whole-Slide Images

Tissue segmentation is an important pre-requisite for efficient and accu...
03/17/2017 ∙ by Péter Bándi, et al. ∙ 0 ∙ share

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Transfer Learning for Domain Adaptation in MRI: Application in Brain Lesion Segmentation

Magnetic Resonance Imaging (MRI) is widely used in routine clinical diag...
02/25/2017 ∙ by Mohsen Ghafoorian, et al. ∙ 0 ∙ share

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

Automatic detection of pulmonary nodules in thoracic computed tomography...
12/23/2016 ∙ by Arnaud Arindra Adiyoso Setio, et al. ∙ 0 ∙ share

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Towards automatic pulmonary nodule management in lung cancer screening with deep learning

The introduction of lung cancer screening programs will produce an unpre...
10/28/2016 ∙ by Francesco Ciompi, et al. ∙ 0 ∙ share

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Deep Multi-scale Location-aware 3D Convolutional Neural Networks for Automated Detection of Lacunes of Presumed Vascular Origin

Lacunes of presumed vascular origin (lacunes) are associated with an inc...
10/24/2016 ∙ by Mohsen Ghafoorian, et al. ∙ 0 ∙ share

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Location Sensitive Deep Convolutional Neural Networks for Segmentation of White Matter Hyperintensities

The anatomical location of imaging features is of crucial importance for...
10/16/2016 ∙ by Mohsen Ghafoorian, et al. ∙ 0 ∙ share

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Student Beats the Teacher: Deep Neural Networks for Lateral Ventricles Segmentation in Brain MR

Ventricular volume and its progression are known to be linked to several...
01/15/2018 ∙ by Mohsen Ghafoorian, et al. ∙ 0 ∙ share

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Iterative fully convolutional neural networks for automatic vertebra segmentation

Precise segmentation of the vertebrae is often required for automatic de...
04/12/2018 ∙ by Nikolas Lessmann, et al. ∙ 0 ∙ share

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Epithelium segmentation using deep learning in H&E-stained prostate specimens with immunohistochemistry as reference standard

Prostate cancer (PCa) is graded by pathologists by examining the archite...
08/17/2018 ∙ by Wouter Bulten, et al. ∙ 0 ∙ share

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GANs for Medical Image Analysis

Generative Adversarial Networks (GANs) and their extensions have carved ...
09/13/2018 ∙ by Salome Kazeminia, et al. ∙ 0 ∙ share

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Chest X-Rays Image Inpainting with Context Encoders

Chest X-rays are one of the most commonly used technologies for medical ...
12/03/2018 ∙ by Davide Belli, et al. ∙ 0 ∙ share

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A large annotated medical image dataset for the development and evaluation of segmentation algorithms

Semantic segmentation of medical images aims to associate a pixel with a...
02/25/2019 ∙ by Amber L. Simpson, et al. ∙ 0 ∙ share

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Computer aided detection of tuberculosis on chest radiographs: An evaluation of the CAD4TB v6 system

There is a growing interest in the automated analysis of chest X-Ray (CX...
03/08/2019 ∙ by Keelin Murphy, et al. ∙ 0 ∙ share

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Evaluation of a deep learning system for the joint automated detection of diabetic retinopathy and age-related macular degeneration

Purpose: To validate the performance of a commercially-available, CE-cer...
03/22/2019 ∙ by Cristina González-Gonzalo, et al. ∙ 0 ∙ share

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Chest X-ray Inpainting with Deep Generative Models

Generative adversarial networks have been successfully applied to inpain...
08/29/2018 ∙ by Ecem Sogancioglu, et al. ∙ 0 ∙ share

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FRODO: Free rejection of out-of-distribution samples: application to chest x-ray analysis

In this work, we propose a method to reject out-of-distribution samples ...
07/02/2019 ∙ by Erdi Çallı, et al. ∙ 0 ∙ share

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Follows Form: Regression from Complete Thoracic Computed Tomography Scans

Chronic Obstructive Pulmonary Disease (COPD) is a leading cause of morbi...
09/26/2019 ∙ by Max Argus, et al. ∙ 0 ∙ share

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mlVIRNET: Multilevel Variational Image Registration Network

We present a novel multilevel approach for deep learning based image reg...
09/22/2019 ∙ by Alessa Hering, et al. ∙ 0 ∙ share

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Function Follows Form: Regression from Complete Thoracic Computed Tomography Scans

Chronic Obstructive Pulmonary Disease (COPD) is a leading cause of morbi...
09/26/2019 ∙ by Max Argus, et al. ∙ 0 ∙ share

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Random smooth gray value transformations for cross modality learning with gray value invariant networks

Random transformations are commonly used for augmentation of the trainin...
03/13/2020 ∙ by Nikolas Lessmann, et al. ∙ 0 ∙ share

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