Bram van Ginneken

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

Nikolas Lessmann, Bram van Ginneken, 2020, ArXiv.

First International Workshop on Pulmonary Image Analysis

Marleen de Bruijne, Christine H. Lorenz, Joseph M. Reinhardt, 2008 .

Normalization of chest radiographs

Bram van Ginneken, Rick H. H. M. Philipsen, Pragnya Maduskar, 2013, Medical Imaging.

Simulation of Nodules and Diffuse Infiltrates in Chest Radiographs Using CT Templates

Max A. Viergever, Bram van Ginneken, Laurens Hogeweg, 2010, MICCAI.

Bram van Ginneken, Yulia Arzhaeva, David M. J. Tax, 2009, Pattern Recognit..

Chest X-Rays Image Inpainting with Context Encoders pdf

Bram van Ginneken, Davide Belli, Shi Hu, 2018, ArXiv.

Automatic age-related macular degeneration detection and staging

Bram van Ginneken, Mark J. J. P. van Grinsven, Yara T. E. Lechanteur, 2013, Medical Imaging.

Vertebra partitioning with thin-plate spline surfaces steered by a convolutional neural network

Max A. Viergever, Nikolas Lessmann, Bram van Ginneken, 2019 .

Segmentation of arteries and veins on 4D CT perfusion scans for constructing arteriograms and venograms

Bram van Ginneken, Adriënne Mendrik, Evert-Jan Vonken, 2009, Medical Imaging.

Chest CT Super-resolution and Domain-adaptation using Memory-efficient 3D Reversible GANs

Bram van Ginneken, Tycho F.A. van der Ouderaa, Daniel E. Worrall, 2019, 1908.00295.

Evaluation of prostate segmentation algorithms for MRI: The PROMISE12 challenge

Florian Jung, Christos Davatzikos, Dean C. Barratt, 2014, Medical Image Anal..

GANs for Medical Image Analysis pdf

Nassir Navab, Arjan Kuijper, Shadi Albarqouni, 2018, Artif. Intell. Medicine.

Combining Automated Image Analysis with Obstetric Sweeps for Prenatal Ultrasound Imaging in Developing Countries

Bram van Ginneken, Thomas L. A. van den Heuvel, Hezkiel Petros, 2017, BIVPCS/POCUS@MICCAI.

Improving weakly-supervised lesion localization with iterative saliency map refinement

Bram van Ginneken, Clara I. Sánchez, Cristina González-Gonzalo, 2018 .

Automated Segmentation of Abdominal Aortic Aneurysms in Multi-spectral MR Images

Max A. Viergever, Marleen de Bruijne, Wiro J. Niessen, 2003, MICCAI.

Multi-Atlas-Based Segmentation With Local Decision Fusion—Application to Cardiac and Aortic Segmentation in CT Scans

Max A. Viergever, Bram van Ginneken, Marius Staring, 2009, IEEE Transactions on Medical Imaging.

Image Classification from Generalized Image Distance Features: Application to Detection of Interstitial Disease in Chest Radiographs

Bram van Ginneken, Yulia Arzhaeva, David M. J. Tax, 2006, 18th International Conference on Pattern Recognition (ICPR'06).

Segmentation of the posterior ribs in chest radiographs using iterated contextual pixel classification

Bram van Ginneken, Marco Loog, B. Ginneken, 2006, IEEE Transactions on Medical Imaging.

Automatic rib segmentation and labeling in computed tomography scans using a general framework for detection, recognition and segmentation of objects in volumetric data

Max A. Viergever, Bram van Ginneken, Joes Staal, 2007, Medical Image Anal..

Comparative study of retinal vessel segmentation methods on a new publicly available database

Bram van Ginneken, Marco Loog, Meindert Niemeijer, 2004, SPIE Medical Imaging.

Assessing the skeletal age from a hand radiograph: automating the Tanner-Whitehouse method

Max A. Viergever, Bram van Ginneken, Meindert Niemeijer, 2003, SPIE Medical Imaging.

Deep learning based automatic liver tumor segmentation in CT with shape-based post-processing

Hans Meine, Jan Hendrik Moltz, Bram van Ginneken, 2018 .

Why rankings of biomedical image analysis competitions should be interpreted with care

Alejandro F. Frangi, Peter F. Neher, Aaron Carass, 2018, Nature Communications.

Global and Local Multi-valued Dissimilarity-Based Classification: Application to Computer-Aided Detection of Tuberculosis

Max A. Viergever, Bram van Ginneken, Laurens Hogeweg, 2009, MICCAI.

Localized Energy-Based Normalization of Medical Images: Application to Chest Radiography

Bram van Ginneken, Rick H. H. M. Philipsen, Pragnya Maduskar, 2015, IEEE Transactions on Medical Imaging.

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

Nico Karssemeijer, Elena Marchiori, Purang Abolmaesumi, 2017, MICCAI.

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

Bram van Ginneken, Yara T. E. Lechanteur, Clara I. Sánchez, 2019, Acta ophthalmologica.

Improved classification of pulmonary nodules by automated detection of benign subpleural lymph nodes

Bram van Ginneken, Eva M. van Rikxoort, Mathias Prokop, 2006, 3rd IEEE International Symposium on Biomedical Imaging: Nano to Macro, 2006..

Automatic Segmentation of the Pulmonary Lobes From Chest CT Scans Based on Fissures, Vessels, and Bronchi

Bram van Ginneken, Jan-Martin Kuhnigk, Michael Schmidt, 2013, IEEE Transactions on Medical Imaging.

Bag-of-Frequencies: A Descriptor of Pulmonary Nodules in Computed Tomography Images

Bram van Ginneken, Pim A. de Jong, Colin Jacobs, 2015, IEEE Transactions on Medical Imaging.

Multi-scale texture classification from generalized locally orderless images

Bram van Ginneken, Bart M. ter Haar Romeny, B. Ginneken, 2003, Pattern Recognit..

Suppression of Translucent Elongated Structures: Applications in Chest Radiography

Bram van Ginneken, Laurens Hogeweg, Clara I. Sánchez, 2013, IEEE Transactions on Medical Imaging.

Automated age-related macular degeneration classification in OCT using unsupervised feature learning

Bram van Ginneken, Rick H. H. M. Philipsen, Mark J. J. P. van Grinsven, 2015, Medical Imaging.

Dimensionality Reduction by Canonical Contextual Correlation Projections

Robert P. W. Duin, Bram van Ginneken, Marco Loog, 2004, ECCV.

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

Bram van Ginneken, Jeroen van der Laak, Johannes Lotz, 2018, Scientific Reports.

Segmentation of the Optic Disc, Macula and Vascular Arch in Fundus Photographs

Bram van Ginneken, Meindert Niemeijer, Michael D. Abràmoff, 2007, IEEE Transactions on Medical Imaging.

Vessel segmentation in 3D spectral OCT scans of the retina

Milan Sonka, Bram van Ginneken, Mona Kathryn Garvin, 2008, SPIE Medical Imaging.

Filter learning: Application to suppression of bony structures from chest radiographs

Bram van Ginneken, Arnold M. R. Schilham, Marco Loog, 2006, Medical Image Anal..

Active-shape-model-based segmentation of abdominal aortic aneurysms in CTA images

Max A. Viergever, Marleen de Bruijne, Wiro J. Niessen, 2002, SPIE Medical Imaging.

Automatic determination of the artery vein ratio in retinal images

Bram van Ginneken, Meindert Niemeijer, Michael D. Abràmoff, 2010, Medical Imaging.

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

Bram van Ginneken, Caroline C. W. Klaver, Clara I. Sánchez, 2019, ArXiv.

Image Denoising with k-nearest Neighbor and Support Vector Regression

Bram van Ginneken, Adriënne Mendrik, B. Ginneken, 2006, 18th International Conference on Pattern Recognition (ICPR'06).

Reflectance and Texture of Real-World Surfaces Authors

Shree K. Nayar, Kristin J. Dana, Jan J. Koenderink, 1997, CVPR 1997.

Automatic Coronary Calcium Scoring in Low-Dose Chest Computed Tomography

Max A. Viergever, Bram van Ginneken, Meindert Niemeijer, 2012, IEEE Transactions on Medical Imaging.

Rib suppression in chest radiographs to improve classification of textural abnormalities

Bram van Ginneken, Pim A. de Jong, Laurens E. Hogeweg, 2010, Medical Imaging.

Automatic classification of retinal vessels into arteries and veins

Bram van Ginneken, Meindert Niemeijer, Michael D. Abràmoff, 2009, Medical Imaging.

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

Bram van Ginneken, Hans Pinckaers, Geert Litjens, 2020, IEEE transactions on pattern analysis and machine intelligence.

Automatic detection of subsolid pulmonary nodules in thoracic computed tomography images

Bram van Ginneken, Jan-Martin Kuhnigk, Pim A. de Jong, 2014, Medical Image Anal..

Information Fusion for Diabetic Retinopathy CAD in Digital Color Fundus Photographs

Bram van Ginneken, Meindert Niemeijer, Michael D. Abràmoff, 2009, IEEE Transactions on Medical Imaging.

Automated detection and quantification of micronodules in thoracic CT scans to identify subjects at risk for silicosis

Bram van Ginneken, Pim A. de Jong, Colin Jacobs, 2014, Medical Imaging.

Automatic detection of calcifications in the aorta from abdominal CT scans

Max A. Viergever, Bram van Ginneken, Ivana Isgum, 2003, CARS.

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

Bram van Ginneken, Pim A. de Jong, Mathias Prokop, 2015, Medical Image Anal..

Chest X-ray Inpainting with Deep Generative Models pdf

Bram van Ginneken, Davide Belli, Shi Hu, 2018, ArXiv.

Adversarial Attack Vulnerability of Medical Image Analysis Systems: Unexplored Factors pdf

Marleen de Bruijne, Bram van Ginneken, Laurens Hogeweg, 2020, ArXiv.

Supervised Probabilistic Segmentation of Pulmonary Nodules in CT Scans

Bram van Ginneken, B. Ginneken, 2006, MICCAI.

Stacked Bidirectional Convolutional LSTMs for 3D Non-contrast CT Reconstruction from Spatiotemporal 4D CT

Bram van Ginneken, Mathias Prokop, Rashindra Manniesing, 2018 .

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

Elena Marchiori, Tom Heskes, Bram van Ginneken, 2016, Scientific Reports.

Interactively learning a patient specific k-nearest neighbor classifier based on confidence weighted samples

Jonathan G. Goldin, Bram van Ginneken, Matthew S. Brown, 2010, 2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

Automatic segmentation of the liver in computed tomography scans with voxel classification and atlas matching

Bram van Ginneken, Yulia Arzhaeva, Eva M. van Rikxoort, 2007 .

Pulmonary Nodule Detection in CT Images: False Positive Reduction Using Multi-View Convolutional Networks

Bram van Ginneken, Geert J. S. Litjens, Paul K. Gerke, 2016, IEEE Transactions on Medical Imaging.

Interactive classification of lung tissue in CT scans by combining prior and interactively obtained training data: A simulation study

Max A. Viergever, Bram van Ginneken, Pim A. de Jong, 2012, Proceedings of the 21st International Conference on Pattern Recognition (ICPR2012).

Supervised segmentation by iterated contextual pixel classification

Bram van Ginneken, Marco Loog, 2002, Object recognition supported by user interaction for service robots.

Automatic detection of eye diseases using automated color fundus image analysis

Bram van Ginneken, Mark J. J. P. van Grinsven, Thomas Theelen, 2015 .

On Combining Multiple-Instance Learning and Active Learning for Computer-Aided Detection of Tuberculosis

Bram van Ginneken, Rick H. H. M. Philipsen, Pragnya Maduskar, 2016, IEEE Transactions on Medical Imaging.

Applications of Locally Orderless Images

Bram van Ginneken, Bart M. ter Haar Romeny, 2000, J. Vis. Commun. Image Represent..

Bony Structure Suppression in Chest Radiographs

Bram van Ginneken, Marco Loog, 2006, CVAMIA.

Fovea detection in optical coherence tomography using convolutional neural networks

Bram van Ginneken, Thomas Theelen, Clara I. Sánchez, 2017, Medical Imaging.

Biomedical Image Analysis Challenges (BIAS) Reporting Guideline

Lena Maier-Hein, Annika Reinke, Matthias Eisenmann, 2020 .

Registration of 3D spectral OCT volumes using 3D SIFT feature point matching

Milan Sonka, Bram van Ginneken, Mona Kathryn Garvin, 2009, Medical Imaging.

Automated detection of pulmonary nodules from low-dose computed tomography scans using a two-stage classification system based on local image features

Bram van Ginneken, Arnold M. R. Schilham, Mathias Prokop, 2007, SPIE Medical Imaging.

Interactive shape models

Max A. Viergever, Marleen de Bruijne, Bram van Ginneken, 2003, SPIE Medical Imaging.

Vessel tree extraction using locally optimal paths

Marleen de Bruijne, Bram van Ginneken, Pechin Lo, 2010, 2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

Robust cranial cavity segmentation in CT and CT perfusion images of trauma and suspected stroke patients

Bram van Ginneken, Mathias Prokop, Rashindra Manniesing, 2017, Medical Image Anal..

Texture histograms as a function of irradiation and viewing direction

Kristin J. Dana, Jan J. Koenderink, Bram van Ginneken, 1999, International Journal of Computer Vision.

Noise Reduction in Computed Tomography Scans Using 3-D Anisotropic Hybrid Diffusion With Continuous Switch

Max A. Viergever, Bram van Ginneken, Adriënne Mendrik, 2009, IEEE Transactions on Medical Imaging.

Automatic Segmentation of the Pulmonary Lobes from Fissures, Airways, and Lung Borders: Evaluation of Robustness against Missing Data

Max A. Viergever, Josien P. W. Pluim, Bram van Ginneken, 2009, MICCAI.

Constraining Volume Change in Learned Image Registration for Lung CTs pdf

Stefan Heldmann, Jan Hendrik Moltz, Nikolas Lessmann, 2020, ArXiv.

Reflectance and texture of real-world surfaces

Shree K. Nayar, Kristin J. Dana, Jan J. Koenderink, 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

Normalization of CT scans reconstructed with different kernels to reduce variability in emphysema measurements

Bram van Ginneken, Eva M. van Rikxoort, Leticia Gallardo Estrella, 2013, Medical Imaging: Computer-Aided Diagnosis.

Robust Segmentation and Anatomical Labeling of the Airway Tree from Thoracic CT Scans

Bram van Ginneken, Eva M. van Rikxoort, Wouter Baggerman, 2008, MICCAI.

Semi-automatic Reference Standard Construction for Quantitative Evaluation of Lung CT Registration

Josien P. W. Pluim, Stefan Klein, Bram van Ginneken, 2008, MICCAI.

Deep Learning in Image Diagnostics: Recent Results and Outlook

Bram van Ginneken, B. Ginneken, 2019, ICPRAM.

Fast Convolutional Neural Network Training Using Selective Data Sampling: Application to Hemorrhage Detection in Color Fundus Images

Bram van Ginneken, Mark J. J. P. van Grinsven, Thomas Theelen, 2016, IEEE Transactions on Medical Imaging.

Reflectance and texture of real-world surfaces

Shree K. Nayar, Kristin J. Dana, Jan J. Koenderink, 1999, TOGS.

Improving Automated COVID-19 Grading with Convolutional Neural Networks in Computed Tomography Scans: An Ablation Study pdf

Nikolas Lessmann, Bram van Ginneken, Colin Jacobs, 2020, ArXiv.

Using the Fourth Dimension to Distinguish Between Structures for Anisotropic Diffusion Filtering in 4D CT Perfusion Scans

Max A. Viergever, Bram van Ginneken, Adrienne Mendrik, 2014, STIA.

Improving hard exudate detection in retinal images through a combination of local and contextual information

Bram van Ginneken, Meindert Niemeijer, Michael D. Abràmoff, 2010, 2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

Automatic Detection of Tuberculosis in Chest Radiographs Using a Combination of Textural, Focal, and Shape Abnormality Analysis

Bram van Ginneken, Rick H. H. M. Philipsen, Pragnya Maduskar, 2015, IEEE Transactions on Medical Imaging.

Model-based segmentation of abdominal aortic aneurysms in CTA images

Max A. Viergever, Marleen de Bruijne, Wiro J. Niessen, 2003, SPIE Medical Imaging.

Automatic Rib Segmentation in CT Data

Max A. Viergever, Bram van Ginneken, Joes Staal, 2004, ECCV Workshops CVAMIA and MMBIA.

Iterative fully convolutional neural networks for automatic vertebra segmentation and identification

Nikolas Lessmann, Bram van Ginneken, Pim A. de Jong, 2018, Medical Image Anal..

A large-scale evaluation of automatic pulmonary nodule detection in chest CT using local image features and k-nearest-neighbour classification

Bram van Ginneken, Arnold M. R. Schilham, Mathias Prokop, 2009, Medical Image Anal..

Fully Automatic Volume Measurement of the Spleen at CT Using Deep Learning.

Bram van Ginneken, Colin Jacobs, Mathias Prokop, 2020, Radiology. Artificial intelligence.

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

Nico Karssemeijer, Bram van Ginneken, Geert J. S. Litjens, 2017, Journal of medical imaging.

A pattern recognition approach to automated coronary calcium scoring

Bram van Ginneken, Mathias Prokop, Ivana Isgum, 2004, Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004..

Optimization Strategies for Interactive Classification of Interstitial Lung Disease Textures

Max A. Viergever, Bram van Ginneken, Pim A. de Jong, 2016, Front. ICT.

Evaluation of Registration Methods on Thoracic CT: The EMPIRE10 Challenge

Brian B. Avants, D. Louis Collins, Nikos Paragios, 2011, IEEE Transactions on Medical Imaging.

Deep multi-scale location-aware 3D convolutional neural networks for automated detection of lacunes of presumed vascular origin

Nico Karssemeijer, Elena Marchiori, Tom Heskes, 2016, NeuroImage: Clinical.

A pattern recognition approach to enhancing structures in 3D CT data

Bram van Ginneken, Eva M. van Rikxoort, 2006, Medical Imaging: Image Processing.

Supervised quality assessment of medical image registration: Application to intra-patient CT lung registration

Josien P. W. Pluim, Bram van Ginneken, Keelin Murphy, 2012, Medical Image Anal..

Intracerebral Haemorrhage Segmentation in Non-Contrast CT

Bram van Ginneken, Ajay Patel, Henk A. Marquering, 2019, Scientific Reports.

Lung field segmentation from thin-slice CT scans in presence of severe pathology

Bram van Ginneken, Meindert Niemeijer, Ingrid C. Sluimer, 2004, SPIE Medical Imaging.

Iterative convolutional neural networks for automatic vertebra identification and segmentation in CT images

Bram van Ginneken, Ivana Isgum, Nikolas Leßmann, 2018, Medical Imaging.

Automatic Segmentation of Pulmonary Lobes Robust Against Incomplete Fissures

Max A. Viergever, Josien P. W. Pluim, Bram van Ginneken, 2010, IEEE Transactions on Medical Imaging.

Improving computer-aided diagnosis of interstitial disease in chest radiographs by combining one-class and two-class classifiers

Bram van Ginneken, Yulia Arzhaeva, David M. J. Tax, 2006, SPIE Medical Imaging.

Simulating nodules in chest radiographs with real nodules from multi-slice CT images

Bram van Ginneken, Arnold M. R. Schilham, 2006, SPIE Medical Imaging.

Off-the-shelf convolutional neural network features for pulmonary nodule detection in computed tomography scans

Bram van Ginneken, Colin Jacobs, Francesco Ciompi, 2015, 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI).

Local noise reduction for emphysema scoring in low-dose CT images

Bram van Ginneken, Arnold M. R. Schilham, Mathias Prokop, 2005, SPIE Medical Imaging.

Automatic detection of hemorrhages on color fundus images using deep learning

Bram van Ginneken, Mark J. J. P. van Grinsven, Thomas Theelen, 2016 .

Non-uniform patch sampling with deep convolutional neural networks for white matter hyperintensity segmentation

Nico Karssemeijer, Elena Marchiori, Tom Heskes, 2016, 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI).

Large scale deep learning for computer aided detection of mammographic lesions

Nico Karssemeijer, Bram van Ginneken, Geert J. S. Litjens, 2017, Medical Image Anal..

Classifying convex sets for vessel detection in retinal images

Max A. Viergever, Bram van Ginneken, Stiliyan Kalitzin, 2002, Proceedings IEEE International Symposium on Biomedical Imaging.

Adversarial cycle-consistent synthesis of cerebral microbleeds for data augmentation pdf

Bram van Ginneken, Rashindra Manniesing, Khrystyna Faryna, 2021, ArXiv.

On Combining Algorithms for Deformable Image Registration

Josien P. W. Pluim, Bram van Ginneken, Sascha E. A. Muenzing, 2012, WBIR.

Comparison of different methods for tissue segmentation in histopathological whole-slide images

Bram van Ginneken, Geert J. S. Litjens, Jeroen van der Laak, 2017, 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017).

Automatic coronary calcium scoring in low-dose non-ECG-synchronized thoracic CT scans

Max A. Viergever, Bram van Ginneken, Mathias Prokop, 2010, Medical Imaging.

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

Hao Chen, Pheng-Ann Heng, Bram van Ginneken, 2016, Medical Image Anal..

Retinopathy Online Challenge: Automatic Detection of Microaneurysms in Digital Color Fundus Photographs

Qin Li, Jane You, Fakhri Karray, 2010, IEEE Transactions on Medical Imaging.

Automatic Detection of the Optic Disc, Fovea and Vacular Arch in Digital Color Photographs of the Retina

Bram van Ginneken, Meindert Niemeijer, Michael D. Abràmoff, 2005, BMVC.

Automated Gleason Grading of Prostate Biopsies using Deep Learning pdf

Bram van Ginneken, Jeroen van der Laak, Hester van Boven, 2019, ArXiv.

DIRBoost: An algorithm for boosting deformable image registration

Josien P. W. Pluim, Bram van Ginneken, Sascha E. A. Muenzing, 2012, 2012 9th IEEE International Symposium on Biomedical Imaging (ISBI).

Function Follows Form: Regression from Complete Thoracic Computed Tomography Scans pdf

Max Argus, Bram van Ginneken, Cornelia Schaefer-Prokop, 2019, ArXiv.

Noise filtering in thin-slice 4D cerebral CT perfusion scans

Bram van Ginneken, Jan-Willem Dankbaar, Adriënne Mendrik, 2010, Medical Imaging.

Automatic detection of abnormalities in chest radiographs using local texture analysis

Kunio Doi, Max A. Viergever, Bram van Ginneken, 2002, IEEE Transactions on Medical Imaging.

Automatic segmentation of pulmonary vasculature in thoracic CT scans with local thresholding and airway wall removal

Bram van Ginneken, Evelien van Dongen, B. Ginneken, 2010, 2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

Automatic Segmentation of Pulmonary Segments From Volumetric Chest CT Scans

Bram van Ginneken, Eva M. van Rikxoort, Bartjan de Hoop, 2009, IEEE Transactions on Medical Imaging.

Automatic delineation of ribs in frontal chest radiographs

Bram van Ginneken, Bart M. ter Haar Romeny, 2000, Medical Imaging: Image Processing.

Multi-scale Nodule Detection in Chest Radiographs

Bram van Ginneken, Arnold M. R. Schilham, Marco Loog, 2003, MICCAI.

Deep convolutional neural networks for automatic coronary calcium scoring in a screening study with low-dose chest CT

Max A. Viergever, Bram van Ginneken, Pim A. de Jong, 2016, SPIE Medical Imaging.

Automated interpretation of prenatal ultrasound using a predefined acquisition protocol in resource-limited countries

Bram van Ginneken, Chris L. de Korte, Thomas L. A. van den Heuvel, 2019 .

REALISE: reconstruction of REALity from Image SEquences

Jan J. Koenderink, Bram van Ginneken, Frederic Fol Leymarie, 1996, Proceedings of 3rd IEEE International Conference on Image Processing.

The importance of stain normalization in colorectal tissue classification with convolutional networks

Bram van Ginneken, Geert J. S. Litjens, Jeroen van der Laak, 2017, 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017).

The Liver Tumor Segmentation Benchmark (LiTS) pdf

Hao Chen, Leo Joskowicz, Alexandre Hostettler, 2019, Medical Image Anal..

Computer analysis of computed tomography scans of the lung: a survey

Bram van Ginneken, Arnold M. R. Schilham, Mathias Prokop, 2006, IEEE Transactions on Medical Imaging.

Automated Measurement of the Arteriolar-to-Venular Width Ratio in Digital Color Fundus Photographs

Bram van Ginneken, Meindert Niemeijer, Michael D. Abràmoff, 2011, IEEE Transactions on Medical Imaging.

Comparison and Evaluation of Methods for Liver Segmentation From CT Datasets

Martin Styner, Jacob D. Furst, Thomas Lange, 2009, IEEE Transactions on Medical Imaging.

Active Learning for an Efficient Training Strategy of Computer-Aided Diagnosis Systems: Application to Diabetic Retinopathy Screening

Bram van Ginneken, Clara I. Sánchez, Meindert Niemeijer, 2010, MICCAI.

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

Isabel Ramos, Bram van Ginneken, Colin Jacobs, 2018, Scientific Reports.

Comparing and combining algorithms for computer-aided detection of pulmonary nodules in computed tomography scans: The ANODE09 study

Ilaria Gori, Hiroshi Fujita, Bram van Ginneken, 2010, Medical Image Anal..

Image structure clustering for image quality verification of color retina images in diabetic retinopathy screening

Bram van Ginneken, Meindert Niemeijer, Michael D. Abràmoff, 2006, Medical Image Anal..

Student beats the teacher: deep neural networks for lateral ventricles segmentation in brain MR

Nico Karssemeijer, Bram van Ginneken, Bram Platel, 2018, Medical Imaging.

Anisotropic 3D Multi-Stream CNN for Accurate Prostate Segmentation from Multi-Planar MRI

Hans Meine, Bram van Ginneken, Horst K. Hahn, 2020, Comput. Methods Programs Biomed..

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

Alejandro F. Frangi, Peter F. Neher, Klaus H. Maier-Hein, 2018, ArXiv.

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

Ronald M. Summers, M. Jorge Cardoso, Lena Maier-Hein, 2019, ArXiv.

On Combining Computer-Aided Detection Systems

Max A. Viergever, Bram van Ginneken, Marco Loog, 2011, IEEE Transactions on Medical Imaging.

Supervised Content Based Image Retrieval Using Radiology Reports

Max A. Viergever, Aurélio J. C. Campilho, Bram van Ginneken, 2012, ICIAR.

Fast detection of the optic disc and fovea in color fundus photographs

Bram van Ginneken, Meindert Niemeijer, Michael D. Abràmoff, 2009, Medical Image Anal..

A pattern recognition framework for vessel segmentation in 4D CT of the brain

Bram van Ginneken, Ewoud J. Smit, Mathias Prokop, 2013, Medical Imaging.

Adaptive local multi-atlas segmentation: Application to the heart and the caudate nucleus

Max A. Viergever, Josien P. W. Pluim, Stefan Klein, 2010, Medical Image Anal..

A Bag of Words approach for discriminating between retinal images containing exudates or drusen

Jayanthi Sivaswamy, Bram van Ginneken, Arunava Chakravarty, 2013, 2013 IEEE 10th International Symposium on Biomedical Imaging.

Computer-aided diagnosis in chest imaging: how to improve performance and avoid reinventing the wheel

Bram van Ginneken, 2010, ISBI.

Automatic detection of red lesions in digital color fundus photographs

Bram van Ginneken, Meindert Niemeijer, Michael D. Abràmoff, 2005, IEEE Transactions on Medical Imaging.

Hybrid diffusion compared with existing diffusion schemes on simulated low dose CT scans

Max A. Viergever, Bram van Ginneken, Arnold M. R. Schilham, 2006, 3rd IEEE International Symposium on Biomedical Imaging: Nano to Macro, 2006..

Segmenting the posterior ribs in chest radiographs by iterated contextual pixel classification

Max A. Viergever, Bram van Ginneken, Marco Loog, 2003, SPIE Medical Imaging.

Applications of Locally Orderless Images

Bram van Ginneken, Bart M. ter Haar Romeny, B. Ginneken, 1999, J. Vis. Commun. Image Represent..

Automatic detection of pleural effusion in chest radiographs

Bram van Ginneken, Rick H. H. M. Philipsen, Pragnya Maduskar, 2016, Medical Image Anal..

Computer-aided diagnosis in chest radiography: a survey

Max A. Viergever, Bram van Ginneken, Bart M. ter Haar Romeny, 2001, IEEE Transactions on Medical Imaging.

Potential of a Standalone Computer-Aided Detection System for Breast Cancer Detection in Screening Mammography

Nico Karssemeijer, Bram van Ginneken, Clara I. Sánchez, 2012, Digital Mammography / IWDM.

Content-Based Image Retrieval by Metric Learning From Radiology Reports: Application to Interstitial Lung Diseases

Max A. Viergever, Isabel Ramos, Aurélio J. C. Campilho, 2016, IEEE Journal of Biomedical and Health Informatics.

Dimensionality reduction of image features using the canonical contextual correlation projection

Robert P. W. Duin, Bram van Ginneken, Marco Loog, 2005, Pattern Recognit..

Evaluation of 4D-CT Lung Registration

Cristian Lorenz, Sven Kabus, Josien P. W. Pluim, 2009, MICCAI.

Front Matter: Volume 8315

Bram van Ginneken, Carol L. Novak, B. Ginneken, 2012, Medical Imaging: Computer-Aided Diagnosis.

Active shape model segmentation with optimal features

Alejandro F. Frangi, Max A. Viergever, Bram van Ginneken, 2002, IEEE Transactions on Medical Imaging.

A survey on deep learning in medical image analysis

Bram van Ginneken, Geert J. S. Litjens, Clara I. Sánchez, 2017, Medical Image Anal..

Multiple-instance learning for computer-aided detection of tuberculosis

Bram van Ginneken, Rick H. H. M. Philipsen, Pragnya Maduskar, 2014, Medical Imaging.

Segmentation of anatomical structures in chest radiographs using supervised methods: a comparative study on a public database

Bram van Ginneken, Marco Loog, Mikkel B. Stegmann, 2006, Medical Image Anal..

Computer-Aided Detection of Ground Glass Nodules in Thoracic CT Images Using Shape, Intensity and Context Features

Bram van Ginneken, Pim A. de Jong, Clara I. Sánchez, 2011, MICCAI.

Static posterior probability fusion for signal detection: applications in the detection of interstitial diseases in chest radiographs

Bram van Ginneken, Marco Loog, M. Loog, 2004, Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004..

Pixel position regression - application to medical image segmentation

Bram van Ginneken, Marco Loog, 2004, Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004..

A computer-aided diagnosis system for detection of lung nodules in chest radiographs with an evaluation on a public database

Bram van Ginneken, Arnold M. R. Schilham, Marco Loog, 2006, Medical Image Anal..

Effect of image variation on computer-aided detection systems

Bram van Ginneken, Rick H. H. M. Philipsen, Pragnya Maduskar, 2014, Medical Imaging.

Automatic cerebrospinal fluid segmentation in non-contrast CT images using a 3D convolutional network

Bram van Ginneken, Mathias Prokop, Rashindra Manniesing, 2017, Medical Imaging.

Contextual computer-aided detection: Improving bright lesion detection in retinal images and coronary calcification identification in CT scans

Bram van Ginneken, Clara I. Sánchez, Meindert Niemeijer, 2012, Medical Image Anal..

Improving airway segmentation in computed tomography using leak detection with convolutional networks

Bram van Ginneken, Eva M. van Rikxoort, Jean-Paul Charbonnier, 2017, Medical Image Anal..

Integrating local voxel classification and global shape models for medical image segmentation

Marleen de Bruijne, Bram van Ginneken, Eva M. van Rikxoort, 2008, Medical Imaging: Image Processing.

Improved texture analysis for automatic detection of tuberculosis (TB) on chest radiographs with bone suppression images

Bram van Ginneken, Pragnya Maduskar, Laurens Hogeweg, 2013, Medical Imaging.

DIRBoost-An algorithm for boosting deformable image registration: Application to lung CT intra-subject registration

Max A. Viergever, Josien P. W. Pluim, Bram van Ginneken, 2014, Medical Image Anal..

MemCNN: A Python/PyTorch package for creating memory-efficient invertible neural networks

Bram van Ginneken, Jonas Teuwen, Rashindra Manniesing, 2019, J. Open Source Softw..

Organ detection in thorax abdomen CT using multi-label convolutional neural networks

Bram van Ginneken, Colin Jacobs, Arnaud Arindra Adiyoso Setio, 2017, Medical Imaging.

Automated localization of costophrenic recesses and costophrenic angle measurement on frontal chest radiographs

Bram van Ginneken, Pragnya Maduskar, Laurens Hogeweg, 2013, Medical Imaging.

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

Bram van Ginneken, Paul K. Gerke, Colin Jacobs, 2016, Scientific Reports.

Automatic classication of pulmonary function in COPD patients using trachea analysis in chest CT scans

Bram van Ginneken, Pim A. de Jong, Eva M. van Rikxoort, 2012, Medical Imaging.

Interactive annotation of textures in thoracic CT scans

Bram van Ginneken, Pim A. de Jong, Mathias Prokop, 2010, Medical Imaging.

Fusion of Local and Global Detection Systems to Detect Tuberculosis in Chest Radiographs

Bram van Ginneken, Laurens Hogeweg, Pim A. de Jong, 2010, MICCAI.

Front Matter: Volume 7963

Ronald M. Summers, Bram van Ginneken, B. Ginneken, 2011, Medical Imaging: Computer-Aided Diagnosis.

Interactive segmentation of abdominal aortic aneurysms in CTA images

Max A. Viergever, Marleen de Bruijne, Wiro J. Niessen, 2004, Medical Image Anal..

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

Bram van Ginneken, Colin Jacobs, Jean-Paul Charbonnier, 2020, ArXiv.

Image-level detection of arterial occlusions in 4D-CTA of acute stroke patients using deep learning

Bram van Ginneken, Rashindra Manniesing, Mathias Prokop, 2020, Medical Image Anal..

Clavicle segmentation in chest radiographs

Bram van Ginneken, Pragnya Maduskar, Laurens Hogeweg, 2012, Medical Image Anal..

Automatic detection of spiculation of pulmonary nodules in computed tomography images

Bram van Ginneken, Colin Jacobs, Mathias Prokop, 2015, Medical Imaging.

Computer-aided detection of lung cancer: combining pulmonary nodule detection systems with a tumor risk prediction model

Bram van Ginneken, Colin Jacobs, Eva M. van Rikxoort, 2015, Medical Imaging.

Interactive lung segmentation in CT scans with severe abnormalities

Bram van Ginneken, Eva M. van Rikxoort, Jan C. Grutters, 2010, 2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

A hardware implementation of a levelset algorithm for carotid lumen segmentation in CTA

Bram van Ginneken, Ning Lin, Rashindra Manniesing, 2013, Medical Imaging.

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

Bram van Ginneken, Ecem Sogancioglu, Keelin Murphy, 2019, ArXiv.

Deep Learning in Medical Imaging: Overview and Future Promise of an Exciting New Technique

Ronald M. Summers, Hayit Greenspan, Bram van Ginneken, 2016 .

Adaptive local multi-atlas segmentation: application to heart segmentation in chest CT scans

Stefan Klein, Bram van Ginneken, Marius Staring, 2008, SPIE Medical Imaging.

Ridge-based vessel segmentation in color images of the retina

Max A. Viergever, Bram van Ginneken, Meindert Niemeijer, 2004, IEEE Transactions on Medical Imaging.

mlVIRNET: Multilevel Variational Image Registration Network

Stefan Heldmann, Bram van Ginneken, Alessa Hering, 2019, MICCAI.

Supervised Enhancement Filters: Application to Fissure Detection in Chest CT Scans

Bram van Ginneken, Eva M. van Rikxoort, Mathias Prokop, 2008, IEEE Transactions on Medical Imaging.

Active learning approach for detection of hard exudates, cotton wool spots, and drusen in retinal images

Bram van Ginneken, Clara I. Sánchez, Meindert Niemeijer, 2009, Medical Imaging.

Towards an Automatic Lung Cancer Screening System in Low Dose Computed Tomography

Isabel Ramos, Bram van Ginneken, Colin Jacobs, 2018, RAMBO+BIA+TIA@MICCAI.

Toward automated segmentation of the pathological lung in CT

Bram van Ginneken, Mathias Prokop, Ingrid Sluimer, 2005, IEEE Transactions on Medical Imaging.

Automatic detection of registration errors for quality assessment in medical image registration

Josien P. W. Pluim, Bram van Ginneken, Keelin Murphy, 2009, Medical Imaging.

Brain tissue segmentation in 4D CT using voxel classification

Bram van Ginneken, Mathias Prokop, Rashindra Manniesing, 2012, Medical Imaging.

Publicly available retinal image data and the use of competitions to standardize algorithm performance comparison

Bram van Ginneken, Meindert Niemeijer, Michael D. Abràmoff, 2009 .

BIAS: Transparent reporting of biomedical image analysis challenges

Lena Maier-Hein, Annika Reinke, Matthias Eisenmann, 2019, Medical Image Analysis.

Local noise weighted filtering for emphysema scoring of low-dose CT images

Bram van Ginneken, Arnold M. R. Schilham, Mathias Prokop, 2006, IEEE Transactions on Medical Imaging.

Automated detection of nodules attached to the pleural and mediastinal surface in low-dose CT scans

Bram van Ginneken, Mathias Prokop, Keelin Murphy, 2008, SPIE Medical Imaging.

Automatic Segmentation of Lung Fields in Chest Radiographs

Bram van Ginneken, Bart M. ter Haar Romeny, 1999, MICCAI.

Extraction of Airways From CT (EXACT'09)

Eric A. Hoffman, Marleen de Bruijne, Rafael Wiemker, 2012, IEEE Transactions on Medical Imaging.

Semi-automatic construction of reference standards for evaluation of image registration

Max A. Viergever, Josien P. W. Pluim, Stefan Klein, 2011, Medical Image Anal..

Handling label noise through model confidence and uncertainty: application to chest radiograph classification

Bram van Ginneken, Ecem Sogancioglu, Ernst Th. Scholten, 2019, Medical Imaging.

Dense Segmentation in Selected Dimensions: Application to Retinal Optical Coherence Tomography

Bram van Ginneken, Clara I. Sánchez, Cristina González-Gonzalo, 2018, MIDL.

A Review of Deep Learning in Medical Imaging: Imaging Traits, Technology Trends, Case Studies With Progress Highlights, and Future Promises pdf

Ronald M. Summers, Jerry L. Prince, Daniel Rueckert, 2020, Proceedings of the IEEE.

A Novel Multiple-Instance Learning-Based Approach to Computer-Aided Detection of Tuberculosis on Chest X-Rays

Bram van Ginneken, Rick H. H. M. Philipsen, Pragnya Maduskar, 2015, IEEE Transactions on Medical Imaging.

Dense Regression Activation Maps For Lesion Segmentation in CT scans of COVID-19 patients pdf

Bram van Ginneken, Colin Jacobs, Weiyi Xie, 2021, ArXiv.

Automated Estimation of Total Lung Volume using Chest Radiographs and Deep Learning pdf

Bram van Ginneken, Ecem Sogancioglu, Mathias Prokop, 2021, Medical physics.

Common Limitations of Image Processing Metrics: A Picture Story pdf

Ronald M. Summers, Sotirios A. Tsaftaris, Lena Maier-Hein, 2021, ArXiv.

Learn2Reg: comprehensive multi-task medical image registration challenge, dataset and evaluation in the era of deep learning pdf

Marc Modat, Yuankai Huo, Ingerid Reinertsen, 2021, ArXiv.

Deep Clustering Activation Maps for Emphysema Subtyping pdf

Bram van Ginneken, Colin Jacobs, Weiyi Xie, 2021, ArXiv.

Anisotropic 3D Multi-Stream CNN for Accurate Prostate Segmentation from Multi-Planar MRI

Hans Meine, Bram van Ginneken, Horst K. Hahn, 2020, Comput. Methods Programs Biomed..

Deep learning with robustness to missing data: A novel approach to the detection of COVID-19

Bram van Ginneken, Keelin Murphy, Tijs Samson, 2021, PloS one.

Structure and position-aware graph neural network for airway labeling pdf

Bram van Ginneken, Colin Jacobs, Jean-Paul Charbonnier, 2022, ArXiv.

Adversarial Attack Vulnerability of Medical Image Analysis Systems: Unexplored Factors

Mitko Veta, Bram van Ginneken, Laurens Hogeweg, 2020, Medical Image Anal..

The Medical Segmentation Decathlon pdf

Yan Wang, Akshay Pai, Daguang Xu, 2021, ArXiv.

CNN-based lung CT registration with multiple anatomical constraints

Stefan Heldmann, Jan Hendrik Moltz, Nikolas Lessmann, 2020, Medical Image Anal..

Automatic detection of calcifications in the aorta from CT scans of the abdomen1

Bram van Ginneken, Ivana Išgum, B. Ginneken, 2004 .

Training a Computer Aided Detection System with Simulated Lung Nodules in Chest Radiographs

Nico Karssemeijer, Bram van Ginneken, Geert J. S. Litjens, 2010 .

Automated segmentation of pulmonary structures in thoracic computed tomography scans: a review

Bram van Ginneken, Eva M. van Rikxoort, B. Ginneken, 2013 .

Software performance in segmenting ground-glass and solid components of subsolid nodules in pulmonary adenocarcinomas

Bram van Ginneken, Jin Mo Goo, Young Tae Kim, 2016, European Radiology.

Nodule volume change estimation in thoracic CT using sphere fitting , morphological segmentation and image registration

Bram van Ginneken, Bartjan de Hoop, Thomas Duindam, 2009 .

A multi-atlas approach to automatic segmentation of the caudate nucleus in MR brain images

Bram van Ginneken, Yulia Arzhaeva, Eva M. van Rikxoort, 2007 .

Second International Workshop on Pulmonary Image Analysis

Christine H. Lorenz, Joseph M. Reinhardt, Bram van Ginneken, 2009 .

Medical Imaging 2011: Computer-Aided Diagnosis

Ronald M. Summers, Bram van Ginneken, 2011 .

Fully automated segmentation of intraretinal cysts in 3D optical coherence tomography

Bram van Ginneken, Mark J. J. P. van Grinsven, Thomas Theelen, 2016 .

Automated segmentation of caudate nucleus in MR brain images with voxel classification

Bram van Ginneken, Yulia Arzhaeva, Eva M. van Rikxoort, 2007 .

Vendor Independent Cyst Segmentation in Retinal SD-OCT Volumes using a Combination of Multiple Scale Convolutional Neural Networks

Bram van Ginneken, Mark J. J. P. van Grinsven, Thomas Theelen, 2015 .

Learning Interstitial Lung Diseases CT Patterns from Reports Keywords

Max A. Viergever, Bram van Ginneken, Aurélio Campilho, 2014 .