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Nico Karssemeijer
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2020 – today
- 2024
- [j42]Nikita Moriakov
, Jim Peters
Improving lesion volume measurements on digital mammograms. Medical Image Anal. 97: 103269 (2024) - 2023
- [i10]Nikita Moriakov, Jim Peters, Ritse Mann, Nico Karssemeijer, Jos van Dijck, Mireille J. M. Broeders, Jonas Teuwen:
Improving Lesion Volume Measurements on Digital Mammograms. CoRR abs/2308.14369 (2023) - 2022
- [i9]Andreas D. Lauritzen, My Catarina von Euler-Chelpin, Elsebeth Lynge, Ilse Vejborg, Mads Nielsen, Nico Karssemeijer, Martin Lillholm:
Robust Cross-vendor Mammographic Texture Models Using Augmentation-based Domain Adaptation for Long-term Breast Cancer Risk. CoRR abs/2212.13439 (2022)
2010 – 2019
- 2019
- [c101]Doiriel Vanegas C., Mahlet A. Birhanu, Nico Karssemeijer, Albert Gubern-Mérida, Michiel Kallenberg
A deep learning method for volumetric breast density estimation from processed full field digital mammograms. Medical Imaging: Computer-Aided Diagnosis 2019: 109500F - [c100]Christiana Balta, Ioannis Sechopoulos
New difference of Gaussian channel-sets for the channelized Hotelling observer? Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2019: 109520C - 2018
- [j41]Alessandro Bria
Improving the Automated Detection of Calcifications Using Adaptive Variance Stabilization. IEEE Trans. Medical Imaging 37(8): 1857-1864 (2018) - [j40]David Tellez
Whole-Slide Mitosis Detection in H&E Breast Histology Using PHH3 as a Reference to Train Distilled Stain-Invariant Convolutional Networks. IEEE Trans. Medical Imaging 37(9): 2126-2136 (2018) - [c99]Claudio Marrocco
Mammogram denoising to improve the calcification detection performance of convolutional nets. IWBI 2018: 107180W - [c98]Alejandro Rodríguez-Ruiz, Ruben E. van Engen, Koen Michielsen
How does wide-angle breast tomosynthesis depict calcifications in comparison to digital mammography? A retrospective observer study. IWBI 2018: 107181T - [c97]Alejandro Rodríguez-Ruiz, Jan-Jurre Mordang, Nico Karssemeijer, Ioannis Sechopoulos
Can radiologists improve their breast cancer detection in mammography when using a deep learning based computer system as decision support? IWBI 2018: 1071803 - [c96]Alessandro Bria, Claudio Marrocco
Improving the automated detection of calcifications by combining deep cascades and deep convolutional nets. IWBI 2018: 1071808 - [c95]Alejandro Rodríguez-Ruiz, Jonas Teuwen, Kaman Chung, Nico Karssemeijer, Margarita Chevalier, Albert Gubern-Mérida, Ioannis Sechopoulos
Pectoral muscle segmentation in breast tomosynthesis with deep learning. Medical Imaging: Computer-Aided Diagnosis 2018: 105752J - [c94]David Tellez, Maschenka Balkenhol, Nico Karssemeijer, Geert Litjens
H&E stain augmentation improves generalization of convolutional networks for histopathological mitosis detection. Medical Imaging: Digital Pathology 2018: 105810Z - [c93]Mohsen Ghafoorian, Jonas Teuwen, Rashindra Manniesing
Student beats the teacher: deep neural networks for lateral ventricles segmentation in brain MR. Medical Imaging: Image Processing 2018: 105742U - [i8]Mohsen Ghafoorian, Jonas Teuwen, Rashindra Manniesing, Frank-Erik de Leeuw, Bram van Ginneken, Nico Karssemeijer, Bram Platel:
Student Beats the Teacher: Deep Neural Networks for Lateral Ventricles Segmentation in Brain MR. CoRR abs/1801.05040 (2018) - [i7]David Tellez, Maschenka Balkenhol, Irene Otte-Höller, Rob van de Loo, Rob Vogels, Peter Bult, Carla Wauters, Willem Vreuls, Suzanne Mol, Nico Karssemeijer, Geert Litjens, Jeroen van der Laak, Francesco Ciompi:
Whole-Slide Mitosis Detection in H&E Breast Histology Using PHH3 as a Reference to Train Distilled Stain-Invariant Convolutional Networks. CoRR abs/1808.05896 (2018) - 2017
- [j39]Thijs Kooi
Large scale deep learning for computer aided detection of mammographic lesions. Medical Image Anal. 35: 303-312 (2017) - [c92]Agnese Marchesi, Alessandro Bria, Claudio Marrocco
The Effect of Mammogram Preprocessing on Microcalcification Detection with Convolutional Neural Networks. CBMS 2017: 207-212 - [c91]Alessandro Bria, Claudio Marrocco
Spatial Enhancement by Dehazing for Detection of Microcalcifications with Convolutional Nets. ICIAP (2) 2017: 288-298 - [c90]Babak Ehteshami Bejnordi, Jimmy Lin, Ben Glass, Maeve Mullooly
Deep learning-based assessment of tumor-associated stroma for diagnosing breast cancer in histopathology images. ISBI 2017: 929-932 - [c89]Thijs Kooi, Nico Karssemeijer:
Deep learning of symmetrical discrepancies for computer-aided detection of mammographic masses. Medical Imaging: Computer-Aided Diagnosis 2017: 101341J - [c88]Thijs Kooi, Jan-Jurre Mordang, Nico Karssemeijer:
Conditional random field modelling of interactions between findings in mammography. Medical Imaging: Computer-Aided Diagnosis 2017: 101341E - [c87]Mohsen Ghafoorian, Alireza Mehrtash, Tina Kapur, Nico Karssemeijer, Elena Marchiori, Mehran Pesteie, Charles R. G. Guttmann, Frank-Erik de Leeuw, Clare M. Tempany, Bram van Ginneken
Transfer Learning for Domain Adaptation in MRI: Application in Brain Lesion Segmentation. MICCAI (3) 2017: 516-524 - [i6]Babak Ehteshami Bejnordi, Jimmy Lin, Ben Glass, Maeve Mullooly, Gretchen L. Gierach, Mark E. Sherman, Nico Karssemeijer, Jeroen van der Laak, Andrew H. Beck:
Deep learning-based assessment of tumor-associated stroma for diagnosing breast cancer in histopathology images. CoRR abs/1702.05803 (2017) - [i5]Mohsen Ghafoorian, Alireza Mehrtash, Tina Kapur, Nico Karssemeijer, Elena Marchiori, Mehran Pesteie, Charles R. G. Guttmann, Frank-Erik de Leeuw, Clare M. Tempany, Bram van Ginneken, Andriy Fedorov, Purang Abolmaesumi, Bram Platel, William M. Wells III:
Transfer Learning for Domain Adaptation in MRI: Application in Brain Lesion Segmentation. CoRR abs/1702.07841 (2017) - [i4]Thijs Kooi, Nico Karssemeijer:
Classifying Symmetrical Differences and Temporal Change in Mammography Using Deep Neural Networks. CoRR abs/1703.07715 (2017) - [i3]Babak Ehteshami Bejnordi, Guido C. A. Zuidhof, Maschenka Balkenhol, Meyke Hermsen, Peter Bult, Bram van Ginneken, Nico Karssemeijer, Geert Litjens, Jeroen van der Laak:
Context-aware stacked convolutional neural networks for classification of breast carcinomas in whole-slide histopathology images. CoRR abs/1705.03678 (2017) - 2016
- [j38]Babak Ehteshami Bejnordi, Geert Litjens
Stain Specific Standardization of Whole-Slide Histopathological Images. IEEE Trans. Medical Imaging 35(2): 404-415 (2016) - [j37]Michiel Kallenberg
Unsupervised Deep Learning Applied to Breast Density Segmentation and Mammographic Risk Scoring. IEEE Trans. Medical Imaging 35(5): 1322-1331 (2016) - [j36]Babak Ehteshami Bejnordi
Automated Detection of DCIS in Whole-Slide H&E Stained Breast Histopathology Images. IEEE Trans. Medical Imaging 35(9): 2141-2150 (2016) - [c86]Mohsen Ghafoorian, Nico Karssemeijer, Tom Heskes
Non-uniform patch sampling with deep convolutional neural networks for white matter hyperintensity segmentation. ISBI 2016: 1414-1417 - [c85]Alessandro Bria, Claudio Marrocco
LUT-QNE: Look-Up-Table Quantum Noise Equalization in Digital Mammograms. Digital Mammography / IWDM 2016: 27-34 - [c84]Jan-Jurre Mordang, Tim Janssen, Alessandro Bria, Thijs Kooi, Albert Gubern-Mérida, Nico Karssemeijer:
Automatic Microcalcification Detection in Multi-vendor Mammography Using Convolutional Neural Networks. Digital Mammography / IWDM 2016: 35-42 - [c83]Thijs Kooi, Albert Gubern-Mérida, Jan-Jurre Mordang, Ritse Mann, Ruud Pijnappel, Klaas Schuur, Ard den Heeten, Nico Karssemeijer:
A Comparison Between a Deep Convolutional Neural Network and Radiologists for Classifying Regions of Interest in Mammography. Digital Mammography / IWDM 2016: 51-56 - [c82]Katharina Holland, Ioannis Sechopoulos
Performance of Breast Cancer Screening Depends on Mammographic Compression. Digital Mammography / IWDM 2016: 183-189 - [c81]Michiel Kallenberg
Learning Density Independent Texture Features. Digital Mammography / IWDM 2016: 299-306 - [c80]Thomy Mertzanidou
Whole Mastectomy Volume Reconstruction from 2D Radiographs and Its Mapping to Histology. Digital Mammography / IWDM 2016: 367-374 - [c79]Alessandro Bria, Claudio Marrocco
Deep Cascade Classifiers to Detect Clusters of Microcalcifications. Digital Mammography / IWDM 2016: 415-422 - [c78]Mehmet Ufuk Dalmis, Albert Gubern-Mérida, Cristina Borelli, Suzan Vreemann, Ritse M. Mann
A fully automated system for quantification of background parenchymal enhancement in breast DCE-MRI. Medical Imaging: Computer-Aided Diagnosis 2016: 97850L - [c77]Albert Gubern-Mérida, Tao Tan, Jan van Zelst, Ritse M. Mann
Automated linking of suspicious findings between automated 3D breast ultrasound volumes. Medical Imaging: Computer-Aided Diagnosis 2016: 97850N - [c76]Katharina Holland, Carla H. van Gils, Johanna O. P. Wanders, Ritse M. Mann
Quantification of mammographic masking risk with volumetric breast density maps: how to select women for supplemental screening. Medical Imaging: Computer-Aided Diagnosis 2016: 97850I - [c75]Mohammad Razavi, Lei Wang, Tao Tan, Nico Karssemeijer, Lars Linsen, Udo Frese
Novel Morphological Features for Non-mass-like Breast Lesion Classification on DCE-MRI. MLMI@MICCAI 2016: 305-312 - [i2]Mohsen Ghafoorian, Nico Karssemeijer, Tom Heskes, Inge van Uden, Clara I. Sánchez, Geert Litjens, Frank-Erik de Leeuw, Bram van Ginneken, Elena Marchiori, Bram Platel:
Location Sensitive Deep Convolutional Neural Networks for Segmentation of White Matter Hyperintensities. CoRR abs/1610.04834 (2016) - [i1]Mohsen Ghafoorian, Nico Karssemeijer, Tom Heskes, Mayra Bergkamp, Joost Wissink, Jiri Obels, Karlijn Keizer, Frank-Erik de Leeuw, Bram van Ginneken, Elena Marchiori, Bram Platel:
Deep Multi-scale Location-aware 3D Convolutional Neural Networks for Automated Detection of Lacunes of Presumed Vascular Origin. CoRR abs/1610.07442 (2016) - 2015
- [j35]Albert Gubern-Mérida, Robert Marti
Automated localization of breast cancer in DCE-MRI. Medical Image Anal. 20(1): 265-274 (2015) - [j34]Albert Gubern-Mérida, Michiel Kallenberg
Breast Segmentation and Density Estimation in Breast MRI: A Fully Automatic Framework. IEEE J. Biomed. Health Informatics 19(1): 349-357 (2015) - [c74]Mohammad Razavi, Lei Wang, Albert Gubern-Mérida, Tatyana Ivanovska, Hendrik Laue, Nico Karssemeijer, Horst K. Hahn:
Towards Accurate Segmentation of Fibroglandular Tissue in Breast MRI Using Fuzzy C-Means and Skin-Folds Removal. ICIAP (1) 2015: 528-536 - [c73]Jan-Jurre Mordang, Nico Karssemeijer:
Vessel segmentation in screening mammograms. Medical Imaging: Computer-Aided Diagnosis 2015: 94140J - [c72]Mohsen Ghafoorian, Nico Karssemeijer, Inge van Uden, Frank-Erik de Leeuw, Tom Heskes
Small white matter lesion detection in cerebral small vessel disease. Medical Imaging: Computer-Aided Diagnosis 2015: 941411 - [c71]Babak Ehteshami Bejnordi, Geert Litjens
A multi-scale superpixel classification approach to the detection of regions of interest in whole slide histopathology images. Medical Imaging: Digital Pathology 2015: 94200H - 2014
- [j33]Alessandro Bria, Nico Karssemeijer, Francesco Tortorella
Learning from unbalanced data: A cascade-based approach for detecting clustered microcalcifications. Medical Image Anal. 18(2): 241-252 (2014) - [j32]Thomy Mertzanidou
MRI to X-ray mammography intensity-based registration with simultaneous optimisation of pose and biomechanical transformation parameters. Medical Image Anal. 18(4): 674-683 (2014) - [j31]Bram Platel, Roel Mus, Tessa Welte, Nico Karssemeijer, Ritse Mann
Automated Characterization of Breast Lesions Imaged With an Ultrafast DCE-MR Protocol. IEEE Trans. Medical Imaging 33(2): 225-232 (2014) - [j30]Geert Litjens
Computer-Aided Detection of Prostate Cancer in MRI. IEEE Trans. Medical Imaging 33(5): 1083-1092 (2014) - [c70]Kersten Petersen, Mads Nielsen, Pengfei Diao, Nico Karssemeijer, Martin Lillholm:
Breast Tissue Segmentation and Mammographic Risk Scoring Using Deep Learning. Digital Mammography / IWDM 2014: 88-94 - [c69]Katharina Holland, Michiel Kallenberg
Stability of Volumetric Tissue Composition Measured in Serial Screening Mammograms. Digital Mammography / IWDM 2014: 239-244 - [c68]Thijs Kooi, Nico Karssemeijer:
Invariant Features for Discriminating Cysts from Solid Lesions in Mammography. Digital Mammography / IWDM 2014: 573-580 - [c67]Jan-Jurre Mordang, Jakob L. Hauth, Gerard J. den Heeten, Nico Karssemeijer:
Automated Labeling of Screening Mammograms with Arterial Calcifications. Digital Mammography / IWDM 2014: 589-596 - [c66]Thomy Mertzanidou
Towards Spatial Correspondence between Specimen and In-vivo Breast Imaging. Digital Mammography / IWDM 2014: 674-680 - [c65]Thijs Kooi, Nico Karssemeijer:
Boosting classification performance in computer aided diagnosis of breast masses in raw full-field digital mammography using processed and screen film images. Medical Imaging: Computer-Aided Diagnosis 2014: 90351B - [c64]Tao Tan, Jan van Zelst, Wei Zhang, Ritse M. Mann, Bram Platel, Nico Karssemeijer:
Chest-wall segmentation in automated 3D breast ultrasound images using thoracic volume classification. Medical Imaging: Computer-Aided Diagnosis 2014: 90351Y - [c63]Babak Ehteshami Bejnordi, Nadya Timofeeva, Irene Otte-Höller, Nico Karssemeijer, Jeroen A. W. M. van der Laak
Quantitative analysis of stain variability in histology slides and an algorithm for standardization. Medical Imaging: Digital Pathology 2014: 904108 - [c62]Mandana Javanshir Moghaddam, Tao Tan, Nico Karssemeijer, Bram Platel:
Automatic nipple detection on 3D images of an automated breast ultrasound system (ABUS). Medical Imaging: Image Processing 2014: 903405 - 2013
- [j29]Marina Velikova, Peter J. F. Lucas, Maurice Samulski, Nico Karssemeijer:
On the interplay of machine learning and background knowledge in image interpretation by Bayesian networks. Artif. Intell. Medicine 57(1): 73-86 (2013) - [j28]Christine Tanner, Guido van Schie, Jan M. Lesniak, Nico Karssemeijer, Gábor Székely:
Improved location features for linkage of regions across ipsilateral mammograms. Medical Image Anal. 17(8): 1265-1272 (2013) - [j27]Tao Tan, Bram Platel, Ritse Mann
Chest wall segmentation in automated 3D breast ultrasound scans. Medical Image Anal. 17(8): 1273-1281 (2013) - [j26]Tao Tan, Bram Platel, Roel Mus, László K. Tabár, Ritse M. Mann
Computer-Aided Detection of Cancer in Automated 3-D Breast Ultrasound. IEEE Trans. Medical Imaging 32(9): 1698-1706 (2013) - [j25]Guido van Schie, Ritse Mann
Generating Synthetic Mammograms From Reconstructed Tomosynthesis Volumes. IEEE Trans. Medical Imaging 32(12): 2322-2331 (2013) - [c61]Tao Tan, Bram Platel, Michael Hicks, Ritse M. Mann, Nico Karssemeijer:
Finding lesion correspondences in different views of automated 3D breast ultrasound. Medical Imaging: Computer-Aided Diagnosis 2013: 86701N - [c60]Medhat M. Riad, Bram Platel, Frank-Erik de Leeuw, Nico Karssemeijer:
Detection of white matter lesions in cerebral small vessel disease. Medical Imaging: Computer-Aided Diagnosis 2013: 867014 - [c59]Wendy J. M. van de Ven, Yipeng Hu, Jelle O. Barentsz
Surface-based prostate registration with biomechanical regularization. Medical Imaging: Image-Guided Procedures 2013: 86711R - [c58]Albert Gubern-Mérida, Lei Wang, Michiel Kallenberg
Breast segmentation in MRI: quantitative evaluation of three methods. Medical Imaging: Image Processing 2013: 86693G - 2012
- [j24]Marina Velikova, Peter J. F. Lucas, Maurice Samulski, Nico Karssemeijer:
A probabilistic framework for image information fusion with an application to mammographic analysis. Medical Image Anal. 16(4): 865-875 (2012) - [j23]Thomy Mertzanidou
MRI to X-ray mammography registration using a volume-preserving affine transformation. Medical Image Anal. 16(5): 966-975 (2012) - [j22]Tao Tan, Bram Platel
Computer-Aided Lesion Diagnosis in Automated 3-D Breast Ultrasound Using Coronal Spiculation. IEEE Trans. Medical Imaging 31(5): 1034-1042 (2012) - [c57]Thomy Mertzanidou
Intensity-Based MRI to X-ray Mammography Registration with an Integrated Fast Biomechanical Transformation. Digital Mammography / IWDM 2012: 48-55 - [c56]Jan M. Lesniak, Guido van Schie, Christine Tanner, Bram Platel, Henkjan J. Huisman
Multimodal Classification of Breast Masses in Mammography and MRI Using Unimodal Feature Selection and Decision Fusion. Digital Mammography / IWDM 2012: 88-95 - [c55]Jelena Bozek
Comparison of Lesion Size Using Area and Volume in Full Field Digital Mammograms. Digital Mammography / IWDM 2012: 96-103 - [c54]Christopher E. Tromans, Guido van Schie, Nico Karssemeijer, Michael Brady:
A Hypothesis-Test Framework for Quantitative Lesion Detection and Diagnosis. Digital Mammography / IWDM 2012: 458-465 - [c53]Jaime Melendez, Clara I. Sánchez, Rianne Hupse, Bram van Ginneken
Potential of a Standalone Computer-Aided Detection System for Breast Cancer Detection in Screening Mammography. Digital Mammography / IWDM 2012: 682-689 - [c52]Geert J. S. Litjens
Automated computer-aided detection of prostate cancer in MR images: from a whole-organ to a zone-based approach. Medical Imaging: Computer-Aided Diagnosis 2012: 83150G - [c51]Tao Tan, Bram Platel, Roel Mus, Nico Karssemeijer:
Detection of breast cancer in automated 3D breast ultrasound. Medical Imaging: Computer-Aided Diagnosis 2012: 831505 - [c50]Albert Gubern-Mérida, Michiel Kallenberg
Segmentation of the Pectoral Muscle in Breast MRI Using Atlas-Based Approaches. MICCAI (2) 2012: 371-378 - [c49]Geert Litjens
A Pattern Recognition Approach to Zonal Segmentation of the Prostate on MRI. MICCAI (2) 2012: 413-420 - 2011
- [j21]Maurice Samulski, Nico Karssemeijer:
Optimizing Case-Based Detection Performance in a Multiview CAD System for Mammography. IEEE Trans. Medical Imaging 30(4): 1001-1009 (2011) - [j20]Sami S. Brandt
An Anatomically Oriented Breast Coordinate System for Mammogram Analysis. IEEE Trans. Medical Imaging 30(10): 1841-1851 (2011) - [c48]Albert Gubern-Mérida, Michiel Kallenberg
Multi-class Probabilistic Atlas-Based Segmentation Method in Breast MRI. IbPRIA 2011: 660-667 - [c47]Christine Tanner, Nico Karssemeijer, Gábor Székely:
Deformation models for registering MR and 3D ultrasound breast images. ISBI 2011: 582-585 - [c46]Geert J. S. Litjens
Automatic computer aided detection of abnormalities in multi-parametric prostate MRI. Medical Imaging: Computer-Aided Diagnosis 2011: 79630T - [c45]Tao Tan, Henkjan J. Huisman
Classification of breast lesions in automated 3D breast ultrasound. Medical Imaging: Computer-Aided Diagnosis 2011: 79630X - [c44]Jan M. Lesniak, Rianne Hupse, Michiel Kallenberg
Computer aided detection of breast masses in mammography using support vector machine classification. Medical Imaging: Computer-Aided Diagnosis 2011: 79631K - [c43]Guido van Schie, Christine Tanner, Nico Karssemeijer:
Estimating corresponding locations in ipsilateral breast tomosynthesis views. Medical Imaging: Computer-Aided Diagnosis 2011: 796306 - [c42]Michiel G. J. Kallenberg
Automatic breast density segmentation based on pixel classification. Medical Imaging: Computer-Aided Diagnosis 2011: 796307 - 2010
- [j19]Sheila Timp, Celia Varela, Nico Karssemeijer:
Computer-aided diagnosis with temporal analysis to improve radiologists' interpretation of mammographic mass lesions. IEEE Trans. Inf. Technol. Biomed. 14(3): 803-808 (2010) - [c41]Nico Karssemeijer:
Computer aided detection in breast imaging: more than perception AID. ISBI 2010: 273 - [c40]Michiel Kallenberg
Comparison of Tilt Correction Methods in Full Field Digital Mammograms. Digital Mammography / IWDM 2010: 191-196 - [c39]Ralph Highnam, Michael Brady, Martin J. Yaffe, Nico Karssemeijer, Jennifer A. Harvey:
Robust Breast Composition Measurement - VolparaTM. Digital Mammography / IWDM 2010: 342-349 - [c38]Guido van Schie, Karin Leifland, Matthew Wallis, Elin Moa, Magnus Hemmendorff, Nico Karssemeijer:
The Effect of Slab Size on Mass Detection Performance of a Screen-Film CAD System in Reconstructed Tomosynthesis Volumes. Digital Mammography / IWDM 2010: 497-504 - [c37]Marina Velikova, Peter J. F. Lucas, Nico Karssemeijer:
Using Local Context Information to Improve Automatic Mammographic Mass Detection. MedInfo 2010: 1291-1295 - [c36]Oscar A. Debats, Nico Karssemeijer, Jelle O. Barentsz
Automated classification of lymph nodes in USPIO-enhanced MR-images: a comparison of three segmentation methods. Medical Imaging: Computer-Aided Diagnosis 2010: 76240Q - [c35]Aliaksei Makarau, Henkjan J. Huisman
Breast MRI intensity non-uniformity correction using mean-shift. Medical Imaging: Computer-Aided Diagnosis 2010: 76242D - [e6]Nico Karssemeijer, Ronald M. Summers:
Medical Imaging 2010: Computer-Aided Diagnosis, San Diego, California, United States, 13-18 February 2010. SPIE Proceedings 7624, SPIE 2010, ISBN 9780819480255 [contents]
2000 – 2009
- 2009
- [j18]Juan Eugenio Iglesias
Robust Initial Detection of Landmarks in Film-Screen Mammograms Using Multiple FFDM Atlases. IEEE Trans. Medical Imaging 28(11): 1815-1824 (2009) - [j17]Rianne Hupse, Nico Karssemeijer:
Use of Normal Tissue Context in Computer-Aided Detection of Masses in Mammograms. IEEE Trans. Medical Imaging 28(12): 2033-2041 (2009) - [c34]Marina Velikova, Maurice Samulski, Peter J. F. Lucas, Nico Karssemeijer:
Causal Probabilistic Modelling for Two-View Mammographic Analysis. AIME 2009: 395-404 - [c33]Nico Karssemeijer, Henkjan J. Huisman
Integrating Biological Knowledge, Novel Imaging Modalities, and Modeling in Breast Cancer Diagnosis. ISBI 2009: 386-389 - [c32]Rianne Hupse, Nico Karssemeijer:
The use of contextual information for computer aided detection of masses in mammograms. Medical Imaging: Computer-Aided Diagnosis 2009: 72600Q - [c31]Michiel Kallenberg
Using volumetric density estimation in computer aided mass detection in mammography. Medical Imaging: Computer-Aided Diagnosis 2009: 72600T - [c30]Guido van Schie, Nico Karssemeijer:
Noise model for microcalcification detection in reconstructed tomosynthesis slices. Medical Imaging: Computer-Aided Diagnosis 2009: 72600M - [e5]Nico Karssemeijer, Maryellen L. Giger:
Medical Imaging 2009: Computer-Aided Diagnosis, Lake Buena Vista (Orlando Area), Florida, United States, 7-12 February 2009. SPIE Proceedings 7260, SPIE 2009, ISBN 9780819475114 [contents] - 2008
- [j16]Boudewijn P. F. Lelieveldt
Information Processing in Medical Imaging 2007. Medical Image Anal. 12(6): 729-730 (2008) - [c29]Marina Velikova, Maurice Samulski, Nico Karssemeijer, Peter J. F. Lucas:
Toward Expert Knowledge Representation for Automatic Breast Cancer Detection. AIMSA 2008: 333-344 - [c28]Marina Velikova, Peter J. F. Lucas, Nivea de Carvalho Ferreira, Maurice Samulski, Nico Karssemeijer:
A decision support system for breast cancer detection in screening programs. ECAI 2008: 658-662 - [c27]Nico Karssemeijer, Andrea Hupse, Maurice Samulski, Michiel Kallenberg
An Interactive Computer Aided Decision Support System for Detection of Masses in Mammograms. Digital Mammography / IWDM 2008: 273-278 - [c26]Michiel Kallenberg
The Effect of Training Sample Size on Performance of Mass Detection. Digital Mammography / IWDM 2008: 343-349 - [c25]Guido van Schie, Nico Karssemeijer:
Detection of Microcalcifications Using a Nonuniform Noise Model. Digital Mammography / IWDM 2008: 378-384 - [c24]Michiel Kallenberg
The effect of training with SFM images in a FFDM CAD system. Medical Imaging: Computer-Aided Diagnosis 2008: 69151O - [c23]Maurice Samulski, Nico Karssemeijer:
Matching mammographic regions in mediolateral oblique and cranio caudal views: a probabilistic approach. Medical Imaging: Computer-Aided Diagnosis 2008: 69151M - [c22]Rianne Hupse, Nico Karssemeijer:
Feature selection for computer-aided detection: comparing different selection criteria. Medical Imaging: Computer-Aided Diagnosis 2008: 691503 - [e4]Maryellen L. Giger, Nico Karssemeijer:
Medical Imaging 2008: Computer-Aided Diagnosis, San Diego, California, United States, 16-21 February 2008. SPIE Proceedings 6915, SPIE 2008, ISBN 9780819470997 [contents] - 2007
- [j15]Peter R. Snoeren, Nico Karssemeijer:
Gray-scale and geometric registration of full-field digital and film-screen mammograms. Medical Image Anal. 11(2): 146-156 (2007) - [j14]Sheila Timp, Celia Varela, Nico Karssemeijer:
Temporal Change Analysis for Characterization of Mass Lesions in Mammography. IEEE Trans. Medical Imaging 26(7): 945-953 (2007) - [c21]Henkjan J. Huisman
Chestwall Segmentation in 3D Breast Ultrasound Using a Deformable Volume Model. IPMI 2007: 245-256 - [c20]Maurice Samulski, Nico Karssemeijer, Peter J. F. Lucas, Perry Groot:
Classification of mammographic masses using support vector machines and Bayesian networks. Medical Imaging: Computer-Aided Diagnosis 2007: 65141J - [e3]Nico Karssemeijer, Boudewijn P. F. Lelieveldt:
Information Processing in Medical Imaging, 20th International Conference, IPMI 2007, Kerkrade, The Netherlands, July 2-6, 2007, Proceedings. Lecture Notes in Computer Science 4584, Springer 2007, ISBN 978-3-540-73272-3 [contents] - [e2]Maryellen L. Giger, Nico Karssemeijer:
Medical Imaging 2007: Computer-Aided Diagnosis, San Diego, CA, United States, 17-22 February 2007. SPIE Proceedings 6514, SPIE 2007, ISBN 9780819466327 [contents] - 2006
- [j13]Sheila Timp, Nico Karssemeijer:
Interval change analysis to improve computer aided detection in mammography. Medical Image Anal. 10(1): 82-95 (2006) - [j12]S. Easter Selvan
Parameter Estimation in Stochastic Mammogram Model by Heuristic Optimization Techniques. IEEE Trans. Inf. Technol. Biomed. 10(4): 685-695 (2006) - [j11]Saskia van Engeland, Peter R. Snoeren, Henkjan J. Huisman
Volumetric breast density estimation from full-field digital mammograms. IEEE Trans. Medical Imaging 25(3): 273-282 (2006) - [c19]Nico Karssemeijer:
Use of Prompt Magnitude in Computer Aided Detection of Masses in Mammograms. Digital Mammography / IWDM 2006: 54-60 - [c18]Saskia van Engeland, Nico Karssemeijer:
Exploitation of Correspondence Between CC and MLO Views in Computer Aided Mass Detection. Digital Mammography / IWDM 2006: 237-242 - [c17]R. Visser, L. Oostveen, Nico Karssemeijer:
Lossless Compression of Digital Mammograms. Digital Mammography / IWDM 2006: 533-540 - 2005
- [c16]Nico Karssemeijer, Peter R. Snoeren, Wei Zhang:
Linearization of Mammograms Using Parameters Derived from Noise Characteristics. IPMI 2005: 258-269 - [c15]Saskia van Engeland, Nico Karssemeijer:
Regrouping initial CAD mass detections to facilitate classification of suspicious regions in mammography. Medical Imaging: Image Processing 2005 - [c14]Peter R. Snoeren, Nico Karssemeijer:
Thickness correction of mammographic images by anisotropic filtering and interpolation of dense tissue. Medical Imaging: Image Processing 2005 - 2004
- [j10]Kristin J. McLoughlin, Philip J. Bones, Nico Karssemeijer:
Noise equalization for detection of microcalcification clusters in direct digital mammogram images. IEEE Trans. Medical Imaging 23(3): 313-320 (2004) - [j9]Peter R. Snoeren, Nico Karssemeijer:
Thickness correction of mammographic images by means of a global parameter model of the compressed breast. IEEE Trans. Medical Imaging 23(7): 799-806 (2004) - 2003
- [j8]Saskia van Engeland, Peter R. Snoeren, Jan H. C. L. Hendriks, Nico Karssemeijer:
A Comparison of Methods for Mammogram Registration. IEEE Trans. Medical Imaging 22(11): 1436-1444 (2003) - [c13]Peter R. Snoeren, Nico Karssemeijer:
Gray Scale Registration of Mammograms Using a Model of Image Acquisition. IPMI 2003: 401-412 - [c12]Celia Varela, J. M. Muller, Nico Karssemeijer:
Mammographic mass characterization using sharpness and lobulation measures. Medical Imaging: Image Processing 2003 - 2001
- [j7]Maryellen L. Giger
Computer-Aided Diagnosis in Medical Imaging. IEEE Trans. Medical Imaging 20(12): 1205-1208 (2001) - [c11]Wouter J. H. Veldkamp, Nico Karssemeijer, Jan H. C. L. Hendriks:
Experiments with radiologists and a fully automated method for characterization of microcalcification clusters. CARS 2001: 586-592 - [c10]Saskia van Engeland, Nico Karssemeijer:
Matching Breast Lesions in Multiple Mammographic Views. MICCAI 2001: 1172-1173 - [c9]Celia Varela, Nico Karssemeijer, Pablo G. Tahoces
Classification of Breast Tumors on Digital Mammograms Using Laws' Texture Features. MICCAI 2001: 1391-1392 - 2000
- [j6]Wouter J. H. Veldkamp, Nico Karssemeijer:
Normalization of Local Contrast in Mammograms. IEEE Trans. Medical Imaging 19(7): 731-738 (2000)
1990 – 1999
- 1999
- [j5]Guido M. te Brake, Nico Karssemeijer:
Single and multiscale detection of masses in digital mammograms. IEEE Trans. Medical Imaging 18(7): 628-639 (1999) - [c8]Nico Karssemeijer:
Local Orientation Distribution as a Function of Spatial Scale for Detection of Masses in Mammograms. IPMI 1999: 280-293 - [c7]Guido M. te Brake, Mark J. Stoutjesdijk, Nico Karssemeijer:
Discrete dynamic contour model for mass segmentation in digital mammograms. Medical Imaging: Image Processing 1999 - [c6]Wouter J. H. Veldkamp, Nico Karssemeijer:
Improved method for detection of microcalcification clusters in digital mammograms. Medical Imaging: Image Processing 1999 - 1998
- [c5]Nico Karssemeijer, Guido M. te Brake:
Combining Single View Features and Asymmetry for Detection of Mass Lesions. Digital Mammography / IWDM 1998: 95-102 - [c4]Guido M. te Brake, Nico Karssemeijer:
Comparison of Three Mass Detection Methods. Digital Mammography / IWDM 1998: 119-126 - [c3]Wouter J. H. Veldkamp, Nico Karssemeijer:
Improved Correction for Signal Dependent Noise Applied to Automatic Detection of Microcalcifications. Digital Mammography / IWDM 1998: 169-176 - [e1]Nico Karssemeijer, Martin Thijssen, Jan H. C. L. Hendriks, Leon van Erning:
Digital Mammography, Fourth International Workshop on Digital Mammograph, IWDM 1998, Nijmegen, The Netherlands, June 1998. Computational Imaging and Vision 13, Springer 1998, ISBN 978-94-010-6234-3 [contents] - 1996
- [j4]Nico Karssemeijer, Guido M. te Brake:
Detection of stellate distortions in mammograms. IEEE Trans. Medical Imaging 15(5): 611-619 (1996) - 1993
- [c2]Nico Karssemeijer:
Adaptive Noise Equalization and Image Analysis in Mammography. IPMI 1993: 472-486 - 1992
- [j3]Nico Karssemeijer:
Stochastic model for automated detection of calcifications in digital mammograms. Image Vis. Comput. 10(6): 369-375 (1992) - 1991
- [c1]Nico Karssemeijer:
A Stochastic Model for Automated Detction of Calculations in Digital Mammograms. IPMI 1991: 227-238 - 1990
- [j2]Nico Karssemeijer:
A statistical method for automatic labeling of tissues in medical images. Mach. Vis. Appl. 3(2): 75-86 (1990) - [j1]Nico Karssemeijer:
A relaxation method for image segmentation using a spatially dependent stochastic model. Pattern Recognit. Lett. 11(1): 13-23 (1990)
Coauthor Index
Michiel Kallenberg
aka: Michiel G. J. Kallenberg
aka: Michiel G. J. Kallenberg
Jeroen van der Laak
aka: Jeroen A. W. M. van der Laak
aka: Jeroen A. W. M. van der Laak
Geert Litjens 0001
aka: Geert J. S. Litjens
aka: Geert J. S. Litjens
Ritse Mann
aka: Ritse M. Mann
aka: Ritse M. Mann
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