Detection of stellate distortions in mammograms N Karssemeijer, GM te Brake IEEE Transactions on Medical Imaging 15 (5), 611-619, 1996 | 380 | 1996 |
Automated classification of parenchymal patterns in mammograms N Karssemeijer Physics in medicine & biology 43 (2), 365, 1998 | 349 | 1998 |
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 | 289 | 2016 |
Computer-aided detection of prostate cancer in MRI G Litjens, O Debats, J Barentsz, N Karssemeijer, H Huisman IEEE transactions on medical imaging 33 (5), 1083-1092, 2014 | 264 | 2014 |
Volumetric breast density estimation from full-field digital mammograms S van Engeland, PR Snoeren, H Huisman, C Boetes, N Karssemeijer IEEE transactions on medical imaging 25 (3), 273-282, 2006 | 257 | 2006 |
Staging urinary bladder cancer after transurethral biopsy: value of fast dynamic contrast-enhanced MR imaging. JO Barentsz, GJ Jager, PB Van Vierzen, JA Witjes, SP Strijk, H Peters, ... Radiology 201 (1), 185-193, 1996 | 232 | 1996 |
A new 2D segmentation method based on dynamic programming applied to computer aided detection in mammography S Timp, N Karssemeijer Medical physics 31 (5), 958-971, 2004 | 223 | 2004 |
Robust Breast Composition Measurement - VolparaTM R Highnam, M Brady, MJ Yaffe, N Karssemeijer, J Harvey International workshop on digital mammography, 342-349, 2010 | 221 | 2010 |
Breast cancer screening with adjunctive ultrasound mammography SP Wang, D Chin, F Rao US Patent 7,556,602, 2009 | 206 | 2009 |
Adaptive noise equalization and recognition of microcalcification clusters in mammograms N Karssemeijer International Journal of Pattern Recognition and Artificial Intelligence 7 …, 1993 | 205 | 1993 |
Computer-aided diagnosis ML Giger, K Suzuki Biomedical information technology, 359-XXII, 2008 | 167 | 2008 |
Breast image analysis for risk assessment, detection, diagnosis, and treatment of cancer ML Giger, N Karssemeijer, JA Schnabel Annual review of biomedical engineering 15, 327-357, 2013 | 166 | 2013 |
Computer-aided detection versus independent double reading of masses on mammograms N Karssemeijer, JDM Otten, ALM Verbeek, JH Groenewoud, ... Radiology 227 (1), 192-200, 2003 | 163 | 2003 |
Single and multiscale detection of masses in digital mammograms GM Te Brake, N Karssemeijer IEEE transactions on medical imaging 18 (7), 628-639, 1999 | 163 | 1999 |
Computer-aided diagnosis in medical imaging. ML Giger, N Karssemeijer, SG Armato | 156 | 2001 |
An automatic method to discriminate malignant masses from normal tissue in digital mammograms1 GM te Brake, N Karssemeijer, JHCL Hendriks Physics in Medicine & Biology 45 (10), 2843, 2000 | 154 | 2000 |
Transfer learning for domain adaptation in mri: Application in brain lesion segmentation M Ghafoorian, A Mehrtash, T Kapur, N Karssemeijer, E Marchiori, ... International conference on medical image computing and computer-assisted …, 2017 | 149 | 2017 |
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), 1-12, 2017 | 145 | 2017 |
Breast cancer screening results 5 years after introduction of digital mammography in a population-based screening program N Karssemeijer, AM Bluekens, D Beijerinck, JJ Deurenberg, M Beekman, ... Radiology 253 (2), 353-358, 2009 | 145 | 2009 |
Stain specific standardization of whole-slide histopathological images BE Bejnordi, G Litjens, N Timofeeva, I Otte-Höller, A Homeyer, ... IEEE transactions on medical imaging 35 (2), 404-415, 2015 | 144 | 2015 |