Articles with public access mandates - Nico KarssemeijerLearn more
Not available anywhere: 15
Breast tissue segmentation and mammographic risk scoring using deep learning
K Petersen, M Nielsen, P Diao, N Karssemeijer, M Lillholm
Breast Imaging: 12th International Workshop, IWDM 2014, Gifu City, Japan …, 2014
Mandates: Danish National Advanced Technology Foundation
Influence of Risk Category and Screening Round on the Performance of an MR Imaging and Mammography Screening Program in Carriers of the BRCA Mutation …
S Vreemann, A Gubern-Mérida, MS Schlooz-Vries, P Bult, CH Van Gils, ...
Radiology 286 (2), 443-451, 2018
Mandates: Netherlands Organisation for Health Research and Development
Compressed sensing for breast MRI: resolving the trade-off between spatial and temporal resolution
S Vreemann, A Rodriguez-Ruiz, D Nickel, L Heacock, L Appelman, ...
Investigative radiology 52 (10), 574-582, 2017
Mandates: Netherlands Organisation for Health Research and Development
A model observer study using acquired mammographic images of an anthropomorphic breast phantom
C Balta, RW Bouwman, I Sechopoulos, MJM Broeders, N Karssemeijer, ...
Medical Physics 45 (2), 655-665, 2018
Mandates: Netherlands Organisation for Scientific Research
Improving computer‐aided detection assistance in breast cancer screening by removal of obviously false‐positive findings
JJ Mordang, A Gubern‐Mérida, A Bria, F Tortorella, G Den Heeten, ...
Medical Physics 44 (4), 1390-1401, 2017
Mandates: Dutch Cancer Society
Deep learning of symmetrical discrepancies for computer-aided detection of mammographic masses
T Kooi, N Karssemeijer
Medical Imaging 2017: Computer-Aided Diagnosis 10134, 388-393, 2017
Mandates: Dutch Cancer Society
Can a channelized Hotelling observer assess image quality in acquired mammographic images of an anthropomorphic breast phantom including image processing?
C Balta, RW Bouwman, I Sechopoulos, MJM Broeders, N Karssemeijer, ...
Medical physics 46 (2), 714-725, 2019
Mandates: Netherlands Organisation for Scientific Research
Improving the automated detection of calcifications by combining deep cascades and deep convolutional nets
A Bria, C Marrocco, M Molinara, B Savelli, JJ Mordang, N Karssemeijer, ...
14th International Workshop on Breast Imaging (IWBI 2018) 10718, 44-51, 2018
Mandates: Dutch Cancer Society
Reliability of MRI tumor size measurements for minimal invasive treatment selection in small breast cancers
WBG Sanderink, M Caballo, LJA Strobbe, P Bult, W Vreuls, DJ Venderink, ...
European Journal of Surgical Oncology 46 (8), 1463-1470, 2020
Mandates: Dutch Cancer Society
Mammogram denoising to improve the calcification detection performance of convolutional nets
C Marrocco, A Bria, V Di Sano, LR Borges, B Savelli, M Molinara, ...
14th International Workshop on Breast Imaging (IWBI 2018) 10718, 219-227, 2018
Mandates: Dutch Cancer Society
Signal template generation from acquired mammographic images for the non-prewhitening model observer with eye-filter
C Balta, RW Bouwman, I Sechopoulos, MJM Broeders, N Karssemeijer, ...
Medical Imaging 2017: Image Perception, Observer Performance, and Technology …, 2017
Mandates: Netherlands Organisation for Scientific Research
Conditional random field modelling of interactions between findings in mammography
T Kooi, JJ Mordang, N Karssemeijer
Medical Imaging 2017: Computer-Aided Diagnosis 10134, 355-362, 2017
Mandates: Dutch Cancer Society
Towards spatial correspondence between specimen and in-vivo breast imaging
T Mertzanidou, J Hipwell, M Dalmis, B Platel, J van der Laak, R Mann, ...
Breast Imaging: 12th International Workshop, IWDM 2014, Gifu City, Japan …, 2014
Mandates: UK Engineering and Physical Sciences Research Council
New difference of Gaussian channel-sets for the channelized Hotelling observer?
C Balta, I Sechopoulos, RW Bouwman, MJM Broeders, N Karssemeijer, ...
Medical Imaging 2019: Image Perception, Observer Performance, and Technology …, 2019
Mandates: Netherlands Organisation for Scientific Research
Assessment of Breast Density
M Brady, R Highnam, N Karssemeijer
Computer-Aided Detection and Diagnosis in Medical Imaging, 96-115, 2015
Mandates: Cancer Research UK, UK Engineering and Physical Sciences Research Council
Available somewhere: 44
Large scale deep learning for computer aided detection of mammographic lesions
T Kooi, G Litjens, B Van Ginneken, A Gubern-Mérida, CI Sánchez, ...
Medical image analysis 35, 303-312, 2017
Mandates: Dutch Cancer Society
Supplemental MRI screening for women with extremely dense breast tissue
MF Bakker, SV de Lange, RM Pijnappel, RM Mann, PHM Peeters, ...
New England Journal of Medicine 381 (22), 2091-2102, 2019
Mandates: Netherlands Organisation for Health Research and Development, Dutch Cancer …
Unsupervised deep learning applied to breast density segmentation and mammographic risk scoring
M Kallenberg, K Petersen, M Nielsen, AY Ng, P Diao, C Igel, CM Vachon, ...
IEEE transactions on medical imaging 35 (5), 1322-1331, 2016
Mandates: Danish National Advanced Technology Foundation, Innovation Fund Denmark
Transfer learning for domain adaptation in mri: Application in brain lesion segmentation
M Ghafoorian, A Mehrtash, T Kapur, N Karssemeijer, E Marchiori, ...
Medical Image Computing and Computer Assisted Intervention− MICCAI 2017 …, 2017
Mandates: US National Institutes of Health, Canadian Institutes of Health Research …
Location sensitive deep convolutional neural networks for segmentation of white matter hyperintensities
M Ghafoorian, N Karssemeijer, T Heskes, IWM van Uden, CI Sanchez, ...
Scientific Reports 7 (1), 5110, 2017
Mandates: Netherlands Organisation for Scientific Research
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