Nico Karssemeijer

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MRI to X-ray mammography registration using a volume-preserving affine transformation

Nico Karssemeijer, Sébastien Ourselin, David J. Hawkes, 2012, Medical Image Anal..

Causal Probabilistic Modelling for Two-View Mammographic Analysis

Nico Karssemeijer, Peter J. F. Lucas, Marina Velikova, 2009, AIME.

Deformation models for registering MR and 3D ultrasound breast images

Nico Karssemeijer, Gábor Székely, Christine Tanner, 2011, 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

Automatic Microcalcification Detection in Multi-vendor Mammography Using Convolutional Neural Networks

Nico Karssemeijer, Alessandro Bria, Jan-Jurre Mordang, 2016, Digital Mammography / IWDM.

Using Information from Two Mammographic Views to Improve Computer-Aided Detection of Mass Lesions

Nico Karssemeijer, Saskia van Engeland, Jan H. C. L. Hendriks, 2003 .

Incorporating texture features in a computer-aided breast lesion diagnosis system for automated three-dimensional breast ultrasound

Nico Karssemeijer, Tao Tan, Bram Platel, 2014, Journal of medical imaging.

Proceedings of the 20th international conference on Information processing in medical imaging

Nico Karssemeijer, Boudewijn P. F. Lelieveldt, N. Karssemeijer, 2007 .

Automated localization of breast cancer in DCE-MRI

Nico Karssemeijer, Robert Marti, Bram Platel, 2015, Medical Image Anal..

Robust Initial Detection of Landmarks in Film-Screen Mammograms Using Multiple FFDM Atlases

Nico Karssemeijer, Juan Eugenio Iglesias, J. E. Iglesias, 2009, IEEE Transactions on Medical Imaging.

Automated computer-aided detection of prostate cancer in MR images: from a whole-organ to a zone-based approach

Nico Karssemeijer, Geert J. S. Litjens, Jelle O. Barentsz, 2012, Medical Imaging.

Normalization of local contrast in mammograms

Nico Karssemeijer, Wouter J. H. Veldkamp, N. Karssemeijer, 2000, IEEE Transactions on Medical Imaging.

Classification of Breast Tumors on Digital Mammograms Using Laws' Texture Features

Nico Karssemeijer, Pablo G. Tahoces, Celia Varela, 2001, MICCAI.

Combining Single View Features and Asymmetry for Detection of Mass Lesions

Nico Karssemeijer, Guido M. te Brake, N. Karssemeijer, 1998, Digital Mammography / IWDM.

Fully automated detection of breast cancer in screening MRI using convolutional neural networks

Nico Karssemeijer, Thijs Kooi, Albert Gubern-Mérida, 2018, Journal of medical imaging.

Thickness correction of mammographic images by means of a global parameter model of the compressed breast

Nico Karssemeijer, Peter R. Snoeren, N. Karssemeijer, 2004, IEEE Transactions on Medical Imaging.

Correlating locations in ipsilateral breast tomosynthesis views using an analytical hemispherical compression model.

Nico Karssemeijer, Christine Tanner, Maurice Samulski, 2011, Physics in medicine and biology.

Compression paddle tilt correction in full-field digital mammograms.

Nico Karssemeijer, Michiel G J Kallenberg, 2012, Physics in medicine and biology.

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

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

Parameter Estimation in Stochastic Mammogram Model by Heuristic Optimization Techniques

Nico Karssemeijer, Jean Sequeira, S. Easter Selvan, 2006, IEEE Transactions on Information Technology in Biomedicine.

Unsupervised Deep Learning Applied to Breast Density Segmentation and Mammographic Risk Scoring

Nico Karssemeijer, Mads Nielsen, Christian Igel, 2016, IEEE Transactions on Medical Imaging.

Spatial Enhancement by Dehazing for Detection of Microcalcifications with Convolutional Nets

Nico Karssemeijer, Alessandro Bria, Claudio Marrocco, 2017, ICIAP.

Can radiologists improve their breast cancer detection in mammography when using a deep learning based computer system as decision support?

Nico Karssemeijer, Ioannis Sechopoulos, Jan-Jurre Mordang, 2018, Other Conferences.

Front Matter: Volume 6915

Nico Karssemeijer, Maryellen L. Giger, M. Giger, 2008, Medical Imaging: Computer-Aided Diagnosis.

Learning from unbalanced data: A cascade-based approach for detecting clustered microcalcifications

Nico Karssemeijer, Alessandro Bria, Francesco Tortorella, 2014, Medical Image Anal..

Use of Prompt Magnitude in Computer Aided Detection of Masses in Mammograms

Nico Karssemeijer, 2006, Digital Mammography / IWDM.

Three-Dimensional Stochastic Organ-Models For Segmentation In CT-Scans

Nico Karssemeijer, 1989, Other Conferences.

Comparison of Lesion Size Using Area and Volume in Full Field Digital Mammograms

Nico Karssemeijer, Mislav Grgic, Jelena Bozek, 2012, Digital Mammography / IWDM.

Stochastic model for automated detection of calcifications in digital mammograms

Nico Karssemeijer, N. Karssemeijer, 1992, Image Vis. Comput..

Information Processing in Medical Imaging 2007

Nico Karssemeijer, Boudewijn P. F. Lelieveldt, 2008, Medical Image Anal..

Chest-wall segmentation in automated 3D breast ultrasound images using thoracic volume classification

Wei Zhang, Nico Karssemeijer, Tao Tan, 2014, Medical Imaging.

Deep learning of symmetrical discrepancies for computer-aided detection of mammographic masses

Nico Karssemeijer, Thijs Kooi, 2017, Medical Imaging.

A relaxation method for image segmentation using a spatially dependent stochastic model

Nico Karssemeijer, N. Karssemeijer, 1990, Pattern Recognit. Lett..

Mammogram denoising to improve the calcification detection performance of convolutional nets

Nico Karssemeijer, Alessandro Bria, Claudio Marrocco, 2018, Other Conferences.

The Effect of Slab Size on Mass Detection Performance of a Screen-Film CAD System in Reconstructed Tomosynthesis Volumes

Nico Karssemeijer, Karin Leifland, Elin Moa, 2010, Digital Mammography / IWDM.

Detection of white matter lesions in cerebral small vessel disease

Nico Karssemeijer, Bram Platel, Frank-Erik de Leeuw, 2013, Medical Imaging.

Matching Breast Lesions in Multiple Mammographic Views

Nico Karssemeijer, Saskia van Engeland, N. Karssemeijer, 2001, MICCAI.

Automated Detection of DCIS in Whole-Slide H&E Stained Breast Histopathology Images

Nico Karssemeijer, Geert J. S. Litjens, Jeroen van der Laak, 2016, IEEE Transactions on Medical Imaging.

Computer-Aided Detection of Prostate Cancer in MRI

Nico Karssemeijer, Geert J. S. Litjens, Jelle O. Barentsz, 2014, IEEE Transactions on Medical Imaging.

Boosting classification performance in computer aided diagnosis of breast masses in raw full-field digital mammography using processed and screen film images

Nico Karssemeijer, Thijs Kooi, 2014, Medical Imaging.

Using deep learning to segment breast and fibroglandular tissue in MRI volumes

Nico Karssemeijer, Geert J. S. Litjens, Albert Gubern-Mérida, 2017, Medical physics.

Interval change analysis to improve computer aided detection in mammography

Nico Karssemeijer, Sheila Timp, N. Karssemeijer, 2006, Medical Image Anal..

Chest wall segmentation in automated 3D breast ultrasound scans

Nico Karssemeijer, Tao Tan, Henkjan J. Huisman, 2013, Medical Image Anal..

Temporal stability of fully automatic volumetric breast density estimation in a large screening population

Nico Karssemeijer, Michiel Kallenberg, N. Karssemeijer, 2013 .

Generating Synthetic Mammograms From Reconstructed Tomosynthesis Volumes

Nico Karssemeijer, Ritse Mann, Guido van Schie, 2013, IEEE Transactions on Medical Imaging.

Breast segmentation in MRI: quantitative evaluation of three methods

Nico Karssemeijer, Robert Marti, Lei Wang, 2013, Medical Imaging.

Gray Scale Registration of Mammograms Using a Model of Image Acquisition

Nico Karssemeijer, Peter R. Snoeren, 2003, IPMI.

The effect of feature selection methods on computer-aided detection of masses in mammograms

Nico Karssemeijer, Rianne Hupse, N. Karssemeijer, 2010, Physics in medicine and biology.

Matching mammographic regions in mediolateral oblique and cranio caudal views: a probabilistic approach

Nico Karssemeijer, Maurice Samulski, 2008, SPIE Medical Imaging.

A fully automated system for quantification of background parenchymal enhancement in breast DCE-MRI

Nico Karssemeijer, Albert Gubern-Mérida, Ritse Mann, 2016, SPIE Medical Imaging.

A multi-atlas approach for prostate segmentation in MR images

Nico Karssemeijer, Geert J. S. Litjens, Henkjan J. Huisman, 2012 .

Deep learning-based assessment of tumor-associated stroma for diagnosing breast cancer in histopathology images

Nico Karssemeijer, Andrew H. Beck, Jimmy Lin, 2017, 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017).

Conditional random field modelling of interactions between findings in mammography

Nico Karssemeijer, Jan-Jurre Mordang, Thijs Kooi, 2017, Medical Imaging.

Classifying Symmetrical Differences and Temporal Change in Mammography Using Deep Neural Networks pdf

Nico Karssemeijer, Thijs Kooi, 2017, ArXiv.

Comparison of Three Mass Detection Methods

Nico Karssemeijer, Guido M. te Brake, 1998, Digital Mammography / IWDM.

Segmentation of the Pectoral Muscle in Breast MRI Using Atlas-Based Approaches

Nico Karssemeijer, Robert Marti, Albert Gubern-Mérida, 2012, MICCAI.

Whole Mastectomy Volume Reconstruction from 2D Radiographs and Its Mapping to Histology

Nico Karssemeijer, David J. Hawkes, John H. Hipwell, 2016, Digital Mammography / IWDM.

Vessel segmentation in screening mammograms

Nico Karssemeijer, Jan-Jurre Mordang, 2015, Medical Imaging.

Using Local Context Information to Improve Automatic Mammographic Mass Detection

Nico Karssemeijer, Peter J. F. Lucas, Marina Velikova, 2010, MedInfo.

Comparison of Tilt Correction Methods in Full Field Digital Mammograms

Nico Karssemeijer, Michiel Kallenberg, 2010, Digital Mammography / IWDM.

Detection of stellate distortions in mammograms

Nico Karssemeijer, Guido M. te Brake, N. Karssemeijer, 1996, IEEE Trans. Medical Imaging.

Small white matter lesion detection in cerebral small vessel disease

Nico Karssemeijer, Elena Marchiori, Tom Heskes, 2015, Medical Imaging.

Experiments with radiologists and a fully automated method for characterization of microcalcification clusters

Nico Karssemeijer, Jan H. C. L. Hendriks, Wouter J. H. Veldkamp, 2001, CARS.

Improving the Automated Detection of Calcifications Using Adaptive Variance Stabilization

Nico Karssemeijer, Alessandro Bria, Claudio Marrocco, 2018, IEEE Transactions on Medical Imaging.

Finding lesion correspondences in different views of automated 3D breast ultrasound

Nico Karssemeijer, Michael Hicks, Tao Tan, 2013, Medical Imaging.

Effect of independent multiple reading of mammograms on detection performance

Nico Karssemeijer, Johannes D. Otten, Antonius A. J. Roelofs, 2004, SPIE Medical Imaging.

Use of Normal Tissue Context in Computer-Aided Detection of Masses in Mammograms

Nico Karssemeijer, Rianne Hupse, N. Karssemeijer, 2009, IEEE Transactions on Medical Imaging.

Pectoral muscle segmentation in breast tomosynthesis with deep learning

Nico Karssemeijer, Ioannis Sechopoulos, Albert Gubern-Mérida, 2018, Medical Imaging.

Breast Segmentation and Density Estimation in Breast MRI: A Fully Automatic Framework

Nico Karssemeijer, Robert Marti, Albert Gubern-Mérida, 2015, IEEE Journal of Biomedical and Health Informatics.

Improved method for detection of microcalcification clusters in digital mammograms

Nico Karssemeijer, Wouter J. H. Veldkamp, 1999, Medical Imaging.

Local Orientation Distribution as a Function of Spatial Scale for Detection of Masses in Mammograms

Nico Karssemeijer, N. Karssemeijer, 1999, IPMI.

Robust Breast Composition Measurement - VolparaTM

Nico Karssemeijer, Michael Brady, Jennifer A. Harvey, 2010, Digital Mammography / IWDM.

Front Matter: Volume 6514

Nico Karssemeijer, Maryellen L. Giger, M. Giger, 2007, Medical Imaging: Computer-Aided Diagnosis.

Common database for research in mammographic image analysis

Nico Karssemeijer, 1993, Electronic Imaging.

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.

Front Matter: Volume 7624

Ronald M. Summers, Nico Karssemeijer, Ronald M. Summers, 2010, Medical Imaging: Computer-Aided Diagnosis.

Classification of breast lesions in automated 3D breast ultrasound

Nico Karssemeijer, Tao Tan, Henkjan J. Huisman, 2011, Medical Imaging.

Breast MRI intensity non-uniformity correction using mean-shift

Nico Karssemeijer, Henkjan J. Huisman, Aliaksei Makarau, 2010, Medical Imaging.

Towards Accurate Segmentation of Fibroglandular Tissue in Breast MRI Using Fuzzy C-Means and Skin-Folds Removal

Nico Karssemeijer, Horst K. Hahn, Albert Gubern-Mérida, 2015, ICIAP.

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.

Quantitative analysis of stain variability in histology slides and an algorithm for standardization

Nico Karssemeijer, Jeroen van der Laak, Babak Ehteshami Bejnordi, 2014, Medical Imaging.

Classifying symmetrical differences and temporal change for the detection of malignant masses in mammography using deep neural networks

Nico Karssemeijer, Thijs Kooi, N. Karssemeijer, 2017, Journal of medical imaging.

Mammographic mass characterization using sharpness and lobulation measures

Nico Karssemeijer, Celia Varela, J. M. Muller, 2003, SPIE Medical Imaging.

The Effect of Training Sample Size on Performance of Mass Detection

Nico Karssemeijer, Michiel Kallenberg, 2008, Digital Mammography / IWDM.

Temporal Change Analysis for Characterization of Mass Lesions in Mammography

Nico Karssemeijer, Celia Varela, Sheila Timp, 2007, IEEE Transactions on Medical Imaging.

A Stochastic Model for Automated Detction of Calculations in Digital Mammograms

Nico Karssemeijer, N. Karssemeijer, 1991, IPMI.

Discrete dynamic contour model for mass segmentation in digital mammograms

Nico Karssemeijer, Guido M. te Brake, Mark J. Stoutjesdijk, 1999, Medical Imaging.

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).

Automated linking of suspicious findings between automated 3D breast ultrasound volumes

Nico Karssemeijer, Tao Tan, Albert Gubern-Mérida, 2016, SPIE Medical Imaging.

Large scale deep learning for computer aided detection of mammographic lesions

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

Optimization of the difference-of-Gaussian channel sets for the channelized Hotelling observer

Nico Karssemeijer, Ioannis Sechopoulos, Ramona W. Bouwman, 2019, Journal of medical imaging.

Improved Correction for Signal Dependent Noise Applied to Automatic Detection of Microcalcifications

Nico Karssemeijer, Wouter J. H. Veldkamp, N. Karssemeijer, 1998, Digital Mammography / IWDM.

Detection of breast cancer in automated 3D breast ultrasound

Nico Karssemeijer, Tao Tan, Bram Platel, 2012, Medical Imaging.

The use of contextual information for computer aided detection of masses in mammograms

Nico Karssemeijer, Rianne Hupse, N. Karssemeijer, 2009, Medical Imaging.

Influence of study design in receiver operating characteristics studies: sequential versus independent reading

Nico Karssemeijer, Bram van Ginneken, Steven Schalekamp, 2014, Journal of medical imaging.

An advanced probabilistic framework for assisting screening mammogram interpretation

Nico Karssemeijer, Peter J. F. Lucas, Marina Velikova, 2010 .

Classification of Breast Tumors in Digitized Mammograms

Nico Karssemeijer, Pablo G. Tahoces, Celia Varela, 2003 .

Lossless Compression of Digital Mammograms

Nico Karssemeijer, R. Visser, L. Oostveen, 2006, Digital Mammography / IWDM.

Detection of Microcalcifications Using a Nonuniform Noise Model

Nico Karssemeijer, Guido van Schie, 2008, Digital Mammography / IWDM.

Automatic breast density segmentation: an integration of different approaches

Nico Karssemeijer, Michiel G J Kallenberg, Mariëtte Lokate, 2011, Physics in medicine and biology.

Automatic computer aided detection of abnormalities in multi-parametric prostate MRI

Nico Karssemeijer, Geert J. S. Litjens, Pieter C. Vos, 2011, Medical Imaging.

Invariant Features for Discriminating Cysts from Solid Lesions in Mammography

Nico Karssemeijer, Thijs Kooi, 2014, Digital Mammography / IWDM.

A multi-scale superpixel classification approach to the detection of regions of interest in whole slide histopathology images

Nico Karssemeijer, Geert J. S. Litjens, Jeroen van der Laak, 2015, Medical Imaging.

A probabilistic framework for image information fusion with an application to mammographic analysis

Nico Karssemeijer, Peter J. F. Lucas, Marina Velikova, 2012, Medical Image Anal..

Single and multiscale detection of masses in digital mammograms

Nico Karssemeijer, Guido M. te Brake, 1999, IEEE Transactions on Medical Imaging.

Signal template generation from acquired mammographic images for the non-prewhitening model observer with eye-filter

Nico Karssemeijer, Ioannis Sechopoulos, Ramona W. Bouwman, 2017, Medical Imaging.

Linearization of Mammograms Using Parameters Derived from Noise Characteristics

Wei Zhang, Nico Karssemeijer, Peter R. Snoeren, 2005, IPMI.

Deep Cascade Classifiers to Detect Clusters of Microcalcifications

Nico Karssemeijer, Alessandro Bria, Claudio Marrocco, 2016, Digital Mammography / IWDM.

Computer-aided detection as a decision assistant in chest radiography

Nico Karssemeijer, Laurens Hogeweg, Peter R. Snoeren, 2011, Medical Imaging.

Medical Imaging 2009: Computer-aided Diagnosis

Nico Karssemeijer, Maryellen L. Giger, 2009 .

A statistical method for automatic labeling of tissues in medical images

Nico Karssemeijer, 2005, Machine Vision and Applications.

A comparison of methods for mammogram registration

Nico Karssemeijer, Peter R. Snoeren, Saskia van Engeland, 2003, IEEE Transactions on Medical Imaging.

Novel Morphological Features for Non-mass-like Breast Lesion Classification on DCE-MRI

Nico Karssemeijer, Gabriel Zachmann, Tao Tan, 2016, MLMI@MICCAI.

An Anatomically Oriented Breast Coordinate System for Mammogram Analysis

Nico Karssemeijer, Mads Nielsen, Sami S. Brandt, 2011, IEEE Transactions on Medical Imaging.

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

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

H and E stain augmentation improves generalization of convolutional networks for histopathological mitosis detection

Nico Karssemeijer, Geert J. S. Litjens, Jeroen van der Laak, 2018, Medical Imaging.

Improved location features for linkage of regions across ipsilateral mammograms

Nico Karssemeijer, Gábor Székely, Christine Tanner, 2013, Medical Image Anal..

An Interactive Computer-aided Detection Workstation for Reading Mammograms

Nico Karssemeijer, Maurice Samulski, Carla Boetes, 2008 .

Information Processing in Medical Imaging, 20th International Conference, IPMI 2007, Kerkrade, The Netherlands, July 2-6, 2007, Proceedings

Nico Karssemeijer, Boudewijn P. F. Lelieveldt, 2007, IPMI.

Computer-aided detection of masses in full-field digital mammography using screen-film mammograms for training

Nico Karssemeijer, Michiel Kallenberg, N. Karssemeijer, 2008, Physics in medicine and biology.

Please use the following format to cite material from this book

Nico Karssemeijer, Maryellen L. Giger, 2009 .

Finding corresponding regions of interest in mediolateral oblique and craniocaudal mammographic views.

Nico Karssemeijer, Sheila Timp, Saskia van Engeland, 2006, Medical physics.

Performance Evaluation of a Digital Reading Station for Screening Mammography

Nico Karssemeijer, Carl J. G. Evertsz, Jan H. C. L. Hendriks, 2003 .

Optimizing Case-Based Detection Performance in a Multiview CAD System for Mammography

Nico Karssemeijer, Maurice Samulski, N. Karssemeijer, 2011, IEEE Transactions on Medical Imaging.

Estimating corresponding locations in ipsilateral breast tomosynthesis views

Nico Karssemeijer, Christine Tanner, Guido van Schie, 2011, Medical Imaging.

Signal Processing Society

Nico Karssemeijer, Milan Sonka, Daniel Rueckert, 2009 .

Computer aided detection in breast imaging: More than perception aid

Nico Karssemeijer, 2010, 2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

Noise model for microcalcification detection in reconstructed tomosynthesis slices

Nico Karssemeijer, Guido van Schie, 2009, Medical Imaging.

A Pattern Recognition Approach to Zonal Segmentation of the Prostate on MRI

Nico Karssemeijer, Geert J. S. Litjens, Henkjan J. Huisman, 2012, MICCAI.

Intensity-Based MRI to X-ray Mammography Registration with an Integrated Fast Biomechanical Transformation

Nico Karssemeijer, Zeike A. Taylor, David J. Hawkes, 2012, Digital Mammography / IWDM.

Feature selection for computer-aided detection: comparing different selection criteria

Nico Karssemeijer, Rianne Hupse, 2008, SPIE Medical Imaging.

Regrouping initial CAD mass detections to facilitate classification of suspicious regions in mammography

Nico Karssemeijer, Saskia van Engeland, N. Karssemeijer, 2005, SPIE Medical Imaging.

The effect of training with SFM images in a FFDM CAD system

Nico Karssemeijer, Michiel Kallenberg, N. Karssemeijer, 2008, SPIE Medical Imaging.

Learning Density Independent Texture Features

Nico Karssemeijer, Christian Igel, Mads Nielsen, 2016, Digital Mammography / IWDM.

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.

New difference of Gaussian channel-sets for the channelized Hotelling observer?

Nico Karssemeijer, Ioannis Sechopoulos, Ramona W. Bouwman, 2019, Medical Imaging.

Volumetric breast density estimation from full-field digital mammograms

Nico Karssemeijer, Peter R. Snoeren, Henkjan J. Huisman, 2006, IEEE Trans. Medical Imaging.

Chestwall Segmentation in 3D Breast Ultrasound Using a Deformable Volume Model

Nico Karssemeijer, Henkjan J. Huisman, 2007, IPMI.

Segmentation of malignant lesions in 3D breast ultrasound using a depth-dependent model.

Nico Karssemeijer, Lei Wang, Tao Tan, 2016, Medical physics.

Automated Characterization of Breast Lesions Imaged With an Ultrafast DCE-MR Protocol

Nico Karssemeijer, Bram Platel, Ritse Mann, 2014, IEEE Transactions on Medical Imaging.

Automatic nipple detection on 3D images of an automated breast ultrasound system (ABUS)

Nico Karssemeijer, Tao Tan, Bram Platel, 2014, Medical Imaging.

Multimodal Classification of Breast Masses in Mammography and MRI Using Unimodal Feature Selection and Decision Fusion

Nico Karssemeijer, Gábor Székely, Christine Tanner, 2012, Digital Mammography / IWDM.

Multi-class Probabilistic Atlas-Based Segmentation Method in Breast MRI

Nico Karssemeijer, Robert Marti, Albert Gubern-Mérida, 2011, IbPRIA.

Integrating biological knowledge, novel imaging modalities, and modeling in breast cancer diagnosis

Nico Karssemeijer, Gábor Székely, David J. Hawkes, 2009, 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

Noise equalization for detection of microcalcification clusters in direct digital mammogram images

Nico Karssemeijer, Philip J. Bones, Kristin J. McLoughlin, 2004, IEEE Transactions on Medical Imaging.

Going from double to single reading for screening exams labeled as likely normal by AI: what is the impact?

Nico Karssemeijer, Alejandro Rodriguez-Ruiz, Christiana Balta, 2020, Other Conferences.

Toward Expert Knowledge Representation for Automatic Breast Cancer Detection

Nico Karssemeijer, Peter J. F. Lucas, Marina Velikova, 2008, AIMSA.

Optimized perception of lesion growth in mammograms using digital display

Nico Karssemeijer, Peter R. Snoeren, Saskia van Engeland, 2003, SPIE Medical Imaging.

Comparison of Three Different Mass Segmentation Methods

Nico Karssemeijer, Jan H. C. L. Hendriks, Sheila Timp, 2003 .

Computer-Aided Diagnosis in Medical Imaging

Nico Karssemeijer, Maryellen L. Giger, Samuel G. Armato, 2001, IEEE Trans. Medical Imaging.

A Hypothesis-Test Framework for Quantitative Lesion Detection and Diagnosis

Nico Karssemeijer, Michael Brady, Christopher E. Tromans, 2012, Digital Mammography / IWDM.

Artiﬁcial Intelligence in Medicine

Nico Karssemeijer, Peter J. F. Lucas, Marina Velikova, 2022 .

Gray-scale and geometric registration of full-field digital and film-screen mammograms

Nico Karssemeijer, Peter R. Snoeren, N. Karssemeijer, 2007, Medical Image Anal..

A deep learning method for volumetric breast density estimation from processed full field digital mammograms

Nico Karssemeijer, Albert Gubern-Mérida, Michiel Kallenberg, 2019, Medical Imaging.

Stain Specific Standardization of Whole-Slide Histopathological Images

Nico Karssemeijer, Geert J. S. Litjens, Jeroen van der Laak, 2016, IEEE Transactions on Medical Imaging.

A Comparison Between a Deep Convolutional Neural Network and Radiologists for Classifying Regions of Interest in Mammography

Nico Karssemeijer, Jan-Jurre Mordang, Thijs Kooi, 2016, Digital Mammography / IWDM.

Breast Tissue Segmentation and Mammographic Risk Scoring Using Deep Learning

Nico Karssemeijer, Mads Nielsen, Martin Lillholm, 2014, Digital Mammography / IWDM.

Improving the automated detection of calcifications by combining deep cascades and deep convolutional nets

Nico Karssemeijer, Alessandro Bria, Claudio Marrocco, 2018, Other Conferences.

Towards Spatial Correspondence between Specimen and In-vivo Breast Imaging

Nico Karssemeijer, David J. Hawkes, John H. Hipwell, 2014, Digital Mammography / IWDM.

Quantification of mammographic masking risk with volumetric breast density maps: how to select women for supplemental screening

Nico Karssemeijer, Ritse Mann, Katharina Holland, 2016, SPIE Medical Imaging.

Thickness correction of mammographic images by anisotropic filtering and interpolation of dense tissue

Nico Karssemeijer, Peter R. Snoeren, 2005, SPIE Medical Imaging.

Automated detection of white matter hyperintensities of all sizes in cerebral small vessel disease.

Nico Karssemeijer, Tom Heskes, Elena Marchiori, 2016, Medical physics.

Automated Labeling of Screening Mammograms with Arterial Calcifications

Nico Karssemeijer, Jan-Jurre Mordang, Jakob L. Hauth, 2014, Digital Mammography / IWDM.

Surface-based prostate registration with biomechanical regularization

Nico Karssemeijer, Dean C. Barratt, Jelle O. Barentsz, 2013, Medical Imaging.

Iso-precision scaling of digitized mammograms to facilitate image analysis

Nico Karssemeijer, Leon J. van Erning, 1991, Medical Imaging.

Automated classification of lymph nodes in USPIO-enhanced MR-images: a comparison of three segmentation methods

Nico Karssemeijer, Jelle O. Barentsz, Henkjan J. Huisman, 2010, Medical Imaging.

Breast tissue segmentation from x-ray radiographs

Nico Karssemeijer, Mads Nielsen, Chen Chen, 2014, Physics in medicine and biology.

The Effect of Mammogram Preprocessing on Microcalcification Detection with Convolutional Neural Networks

Nico Karssemeijer, Alessandro Bria, Claudio Marrocco, 2017, 2017 IEEE 30th International Symposium on Computer-Based Medical Systems (CBMS).

Performance of Breast Cancer Screening Depends on Mammographic Compression

Nico Karssemeijer, Ioannis Sechopoulos, Ritse Mann, 2016, Digital Mammography / IWDM.

Computer-Aided Detection of Cancer in Automated 3-D Breast Ultrasound

Nico Karssemeijer, Tao Tan, Bram Platel, 2013, IEEE Transactions on Medical Imaging.

Medical Imaging 2007: Computer-Aided Diagnosis

Nico Karssemeijer, Maryellen L. Giger, 2007 .

Adaptive Noise Equalization and Image Analysis in Mammography

Nico Karssemeijer, N. Karssemeijer, 1993, IPMI.

Medical Imaging 2008: Computer-Aided Diagnosis

Nico Karssemeijer, Maryellen L. Giger, 2008 .

Whole-Slide Mitosis Detection in H&E Breast Histology Using PHH3 as a Reference to Train Distilled Stain-Invariant Convolutional Networks

Nico Karssemeijer, Francesco Ciompi, Jeroen van der Laak, 2018, IEEE Transactions on Medical Imaging.

ADAPTIVE NOISE EQUALIZATION AND RECOGNITION OF MICROCALCIFICATION CLUSTERS IN MAMMOGRAMS

Nico Karssemeijer, N. Karssemeijer, 1993 .

Computer aided detection of breast masses in mammography using support vector machine classification

Nico Karssemeijer, Gábor Székely, Maurice Samulski, 2011, Medical Imaging.

Mass detection in reconstructed digital breast tomosynthesis volumes with a computer-aided detection system trained on 2D mammograms.

Nico Karssemeijer, Mats Danielsson, Matthew G Wallis, 2013, Medical physics.

LUT-QNE: Look-Up-Table Quantum Noise Equalization in Digital Mammograms

Nico Karssemeijer, Alessandro Bria, Claudio Marrocco, 2016, Digital Mammography / IWDM.

Combining two mammographic projections in a computer aided mass detection method.

Nico Karssemeijer, Saskia van Engeland, N. Karssemeijer, 2007, Medical physics.

How does wide-angle breast tomosynthesis depict calcifications in comparison to digital mammography? A retrospective observer study

Nico Karssemeijer, Koen Michielsen, Ioannis Sechopoulos, 2018, Other Conferences.

Computer-Aided Lesion Diagnosis in Automated 3-D Breast Ultrasound Using Coronal Spiculation

Nico Karssemeijer, Tao Tan, Henkjan J. Huisman, 2012, IEEE Transactions on Medical Imaging.

A decision support system for breast cancer detection in screening programs

Nico Karssemeijer, Peter J. F. Lucas, Marina Velikova, 2008, ECAI.

Computer-Aided Diagnosis With Temporal Analysis to Improve Radiologists’ Interpretation of Mammographic Mass Lesions

Nico Karssemeijer, Celia Varela, Sheila Timp, 2010, IEEE Transactions on Information Technology in Biomedicine.

Exploitation of Correspondence Between CC and MLO Views in Computer Aided Mass Detection

Nico Karssemeijer, Saskia van Engeland, 2006, Digital Mammography / IWDM.

Stability of Volumetric Tissue Composition Measured in Serial Screening Mammograms

Nico Karssemeijer, Ritse Mann, Michiel Kallenberg, 2014, Digital Mammography / IWDM.

Optimized soft-copy display of digitized mammograms

Nico Karssemeijer, Sander van Woudenberg, Jan H. C. L. Hendriks, 2003, SPIE Medical Imaging.

Automatic breast density segmentation based on pixel classification

Nico Karssemeijer, Carla H. van Gils, Michiel G. J. Kallenberg, 2011, Medical Imaging.

Using context for mass detection and classification in mammograms

Nico Karssemeijer, Peter R. Snoeren, Celia Varela, 2005, SPIE Medical Imaging.

Using volumetric density estimation in computer aided mass detection in mammography

Nico Karssemeijer, Michiel Kallenberg, 2009, Medical Imaging.

MRI to X-ray mammography intensity-based registration with simultaneous optimisation of pose and biomechanical transformation parameters

Nico Karssemeijer, Sébastien Ourselin, Zeike A. Taylor, 2014, Medical Image Anal..

Classification of mammographic masses using support vector machines and Bayesian networks

Nico Karssemeijer, Peter J. F. Lucas, Maurice Samulski, 2007, SPIE Medical Imaging.

Front Matter: Volume 7260

Nico Karssemeijer, Maryellen L. Giger, M. Giger, 2009, Medical Imaging: Computer-Aided Diagnosis.

An Interactive Computer Aided Decision Support System for Detection of Masses in Mammograms

Nico Karssemeijer, Maurice Samulski, Gerard J. den Heeten, 2008, Digital Mammography / IWDM.

Sliced alternating DICOM series: convenient visualisation of image fusion on PACS

Nico Karssemeijer, Henkjan Huisman, Wim J. G. Oyen, 2005, European Journal of Nuclear Medicine and Molecular Imaging.

Automated detection of breast cancer in false-negative screening MRI studies from women at increased risk.

Nico Karssemeijer, Bram Platel, Albert Gubern-Mérida, 2016, European journal of radiology.

New reconstruction algorithm for digital breast tomosynthesis: better image quality for humans and computers

Nico Karssemeijer, Ioannis Sechopoulos, Alejandro Rodriguez-Ruiz, 2017, Acta radiologica.

Detection and Diagnosis of Breast Masses in Mammography

Nico Karssemeijer, N. Karssemeijer, 2015 .

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

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

Volumetric breast density affects performance of digital screening mammography

Nico Karssemeijer, Wouter B. Veldhuis, Katharina Holland, 2016, Breast Cancer Research and Treatment.

A method to determine the mammographic regions that show early changes due to the development of breast cancer.

Nico Karssemeijer, Mads Nielsen, Gopal Karemore, 2014, Physics in medicine and biology.

Effect of compression paddle tilt correction on volumetric breast density estimation

Nico Karssemeijer, Gerard J den Heeten, Carla H van Gils, 2012, Physics in medicine and biology.

A regional registration method to find corresponding mass lesions in temporal mammogram pairs.

Nico Karssemeijer, Sheila Timp, Saskia van Engeland, 2005, Medical physics.

Improving computer‐aided detection assistance in breast cancer screening by removal of obviously false‐positive findings

Nico Karssemeijer, Alessandro Bria, Francesco Tortorella, 2017, Medical physics.

Increase in perceived case suspiciousness due to local contrast optimisation in digital screening mammography

Nico Karssemeijer, Wouter J. H. Veldkamp, Mireille J. M. Broeders, 2011, European Radiology.

Computer-aided detection of masses at mammography: interactive decision support versus prompts.

Nico Karssemeijer, Maurice Samulski, Rianne Hupse, 2013, Radiology.

Clinical evaluation of a computer-aided diagnosis system for determining cancer aggressiveness in prostate MRI

Nico Karssemeijer, Geert J. S. Litjens, Jelle O. Barentsz, 2015, European Radiology.

A model observer study using acquired mammographic images of an anthropomorphic breast phantom

Nico Karssemeijer, Ioannis Sechopoulos, Ramona W. Bouwman, 2018, Medical physics.

Using deep convolutional neural networks to identify and classify tumor-associated stroma in diagnostic breast biopsies

Nico Karssemeijer, Andrew H. Beck, Donald L. Weaver, 2018, Modern Pathology.

Effect of independent double and multiple reading of screening mammograms by breast density

Nico Karssemeijer, 2014 .

Multiplanar Reconstructions of 3D Automated Breast Ultrasound Improve Lesion Differentiation by Radiologists.

Nico Karssemeijer, Bram Platel, Ritse M Mann, 2015, Academic radiology.

Using computer-aided detection in mammography as a decision support

Nico Karssemeijer, Maurice Samulski, Rianne Hupse, 2010, European Radiology.

Quantification of masking risk in screening mammography with volumetric breast density maps

Nico Karssemeijer, Katharina Holland, Ritse M. Mann, 2017, Breast Cancer Research and Treatment.

Digital mammography : Nijmegen, 1998

Nico Karssemeijer, 1998 .

Evaluation of the effect of computer-aided classification of benign and malignant lesions on reader performance in automated three-dimensional breast ultrasound.

Nico Karssemeijer, Tao Tan, Bram Platel, 2013, Academic radiology.

Automated analysis of contrast enhancement in breast MRI lesions using mean shift clustering for ROI selection

Nico Karssemeijer, Henkjan Huisman, Jeroen Veltman, 2007, Journal of magnetic resonance imaging : JMRI.

Effect of recall rate on earlier screen detection of breast cancers based on the Dutch performance indicators.

Nico Karssemeijer, Harry J de Koning, Roland Holland, 2005, Journal of the National Cancer Institute.

Importance of comparison of current and prior mammograms in breast cancer screening.

Nico Karssemeijer, Brigitte Séradour, Hans Junkermann, 2007, Radiology.

Bone Suppression Increases the Visibility of Invasive Pulmonary Aspergillosis in Chest Radiographs

Nico Karssemeijer, Bram van Ginneken, Steven Schalekamp, 2014, PloS one.

Computer-aided detection of breast cancers using Haar-like features in automated 3D breast ultrasound.

Nico Karssemeijer, Wei Zhang, Tao Tan, 2015, Medical physics.

Use of prior mammograms in the classification of benign and malignant masses.

Nico Karssemeijer, Celia Varela, Roland Holland, 2005, European journal of radiology.

Analysis of Changes in Masses Using Contrast and Size Measures

Nico Karssemeijer, Sheila Timp, Jan H. C. L. Hendriks, 2003 .

Ultrasonics, Ferroelectrics, and Frequency Control

Nico Karssemeijer, Milan Sonka, Moshe Kam, 2011 .

Biomechanical modeling constrained surface-based image registration for prostate MR guided TRUS biopsy.

Nico Karssemeijer, Yipeng Hu, Dean Barratt, 2015, Medical physics.

Bone suppressed images improve radiologists' detection performance for pulmonary nodules in chest radiographs.

Nico Karssemeijer, Bram van Ginneken, Steven Schalekamp, 2013, European journal of radiology.

Compressed Sensing for Breast MRI: Resolving the Trade-Off Between Spatial and Temporal Resolution

Nico Karssemeijer, Linda Moy, Jan van Zelst, 2017, Investigative radiology.

Volumetric Breast Density Estimation from Full-Field Digital Mammograms: A Validation Study

Nico Karssemeijer, Bram Platel, Albert Gubern-Mérida, 2014, IEEE Transactions on Medical Imaging.

Improved mammographic CAD performance using multi-view information: a Bayesian network framework

Nico Karssemeijer, Marina Velikova, Maurice Samulski, 2009, Physics in medicine and biology.

The value of scatter removal by a grid in full field digital mammography.

Nico Karssemeijer, Wouter J H Veldkamp, N. Karssemeijer, 2003, Medical physics.

A Novel Approach to Contrast-Enhanced Breast Magnetic Resonance Imaging for Screening: High-Resolution Ultrafast Dynamic Imaging

Nico Karssemeijer, Bram Platel, Jan van Zelst, 2014, Investigative radiology.

One-view digital breast tomosynthesis as a stand-alone modality for breast cancer detection: do we need more?

Nico Karssemeijer, Ioannis Sechopoulos, Magnus Dustler, 2017, European Radiology.

Computer-aided detection versus independent double reading of masses on mammograms.

Nico Karssemeijer, Harry J de Koning, Roland Holland, 2003, Radiology.

3D volume reconstruction from serial breast specimen radiographs for mapping between histology and 3D whole specimen imaging

Nico Karssemeijer, David J. Hawkes, John H. Hipwell, 2017, Medical physics.

A novel iterative method for lesion delineation and volumetric quantification with FDG PET

Nico Karssemeijer, Volker Dicken, Aswin L Hoffmann, 2007, Nuclear medicine communications.

MR Imaging as an Additional Screening Modality for the Detection of Breast Cancer in Women Aged 50-75 Years with Extremely Dense Breasts: The DENSE Trial Study Design.

Nico Karssemeijer, Harry J de Koning, Ritse M Mann, 2015, Radiology.

Time to enhancement derived from ultrafast breast MRI as a novel parameter to discriminate benign from malignant breast lesions.

Nico Karssemeijer, Jelle O. Barentsz, Bram Platel, 2017, European journal of radiology.

Robust breast composition measurement - Volpara™

Nico Karssemeijer, Martin J. Yaffe, Jennifer A. Harvey, 2010 .

Dynamic analysis of breast lesions : Can we use the wash-in phase instead of the washout phase ?

Nico Karssemeijer, Henkjan Huisman, Bram Platel, 2011 .

Sonographic Phenotypes of Molecular Subtypes of Invasive Ductal Cancer in Automated 3-D Breast Ultrasound.

Nico Karssemeijer, Tao Tan, Ritse M Mann, 2017, Ultrasound in medicine & biology.

Computer aided analysis of breast MRI enhancement kinetics using mean shift c lustering and multifeature iterative region of interest selection

Nico Karssemeijer, Henkjan Huisman, Carla Boetes, 2012, Journal of magnetic resonance imaging : JMRI.

Standalone computer-aided detection compared to radiologists’ performance for the detection of mammographic masses

Nico Karssemeijer, Maurice Samulski, Rianne Hupse, 2012, European Radiology.

Effect of soft-copy display supported by CAD on mammography screening performance

Nico Karssemeijer, Carl J. G. Evertsz, Sander van Woudenberg, 2005, European Radiology.

Breast cancer screening results 5 years after introduction of digital mammography in a population-based screening program.

Nico Karssemeijer, Ruben van Engen, N. Karssemeijer, 2009, Radiology.

Detection of Masses in Mammograms

Nico Karssemeijer, N. Karssemeijer, 2002 .

Artificial Intelligence–Based Classification of Breast Lesions Imaged With a Multiparametric Breast MRI Protocol With Ultrafast DCE-MRI, T2, and DWI

Nico Karssemeijer, Albert Gubern-Mérida, Ritse Mann, 2019, Investigative radiology.