Browsing by Author "Karssemeijer, N."

Can a channelized Hotelling observer assess image quality in acquired mammographic images of an anthropomorphic breast phantom including image processing?

Balta, C.; Bouwman, Ramona W.; Sechopoulos, I.; Broeders, M.J.M. ; Karssemeijer, N. ; Engen, R.E. van; Veldkamp, W.J.H.

2019, Article / Letter to editor (Medical Physics, vol. 46, iss. 2, (2019), pp. 714-725)

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

Dalmis, M.U.; Gubern Merida, A.; Vreemann, S.; Bult, P. ; Karssemeijer, N. ; Mann, R.M. ; Teuwen, J.J.B.

2019, Article / Letter to editor (Investigative Radiology, vol. 54, iss. 6, (2019), pp. 325-332)

A systematic review on the use of the breast lesion excision system in breast disease

Sanderink, W.B.G.; Laarhuis, B.I.; Strobbe, L.J.A.; Sechopoulos, I.; Bult, P. ; Karssemeijer, N. ; Mann, R.M.

2019, Article / Letter to editor (Insights Into Imaging, vol. 10, iss. 1, (2019), pp. 49)

MRI versus mammography for breast cancer screening in women with familial risk (FaMRIsc): a multicentre, randomised, controlled trial

Saadatmand, Sepideh; Geuzinge, H.Amarens; Rutgers, Emiel J.T.; Mann, R.M. ; Zuidewijn, Diderick B.W.de Roy van; Zonderland, Harmien M.; Karssemeijer, N. ; Oosterwijk, J.C; Koning, H.J. de; Tilanus-Linthorst, Madeleine M.A.

2019, Article / Letter to editor (Lancet Oncology, vol. 20, iss. 8, (2019), pp. 1136-1147)

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

Balta, C.; Bouwman, Ramona W.; Sechopoulos, I.; Broeders, M.J.M. ; Karssemeijer, N. ; Engen, R.E. van; Veldkamp, W.J.H.

2018, Article / Letter to editor (Medical Physics, vol. 45, iss. 2, (2018), pp. 655-665)

The combined effect of mammographic texture and density on breast cancer risk: a cohort study

Wanders, J.O.; Gils, Carla H. van; Karssemeijer, N. ; Holland, K.; Kallenberg, Michiel; Peeters, P.H.M.; Nielsen, M.; Lillholm, M.

2018, Article / Letter to editor (Breast Cancer Research, vol. 20, (2018), article 36)

Improving the Automated Detection of Calcifications Using Adaptive Variance Stabilization

Bria, A.; Marrocco, Claudio; Borges, Lucas R.; Molinara, Mario; Marchesi, Agnese; Mordang, J.J.; Karssemeijer, N. ; Tortorella, F.

2018, Article / Letter to editor (IEEE Transactions on Medical Imaging, vol. 37, iss. 8, (2018), pp. 1857-1864)

Reasons for (non) participation in supplemental population-based MRI breast screening for women with extremely dense breasts

Lange, S.V. de; Bakker, M.F.; Monninkhof, E.M.; Peeters, P.H.M.; Koekkoek-Doll, P.K. de; Mann, R.M. ; Karssemeijer, N. ; Veldhuis, W.B.; Gils, C.H. van

2018, Article / Letter to editor (Clinical Radiology Extra, vol. 73, iss. 8, (2018), pp. 759 e1-759 e9, article 759.e1-759.e9)

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

Dalmis, M.U.; Vreemann, S.; Kooi, T.; Mann, R.M. ; Karssemeijer, N. ; Gubern Merida, A.

2018, Article / Letter to editor (Journal of Medical Imaging, vol. 5, iss. 1, (2018), article 014502)

Multireader Study on the Diagnostic Accuracy of Ultrafast Breast Magnetic Resonance Imaging for Breast Cancer Screening

Zelst, J.C.M. van; Vreemann, S.; Witt, Hans-Joerg; Gubern Merida, A.; Dorrius, Monique D.; Duvivier, K.M.; Lardenoije-Broker, S.; Karssemeijer, N. ; Mann, R.M.

2018, Article / Letter to editor (Investigative Radiology, vol. 53, iss. 10, (2018), pp. 579-586)

The added value of mammography in different age-groups of women with and without BRCA mutation screened with breast MRI

Vreemann, S.; Zelst, J.C.M. van; Schlooz-Vries, M.S. ; Bult, P. ; Hoogerbrugge, N. ; Karssemeijer, N. ; Gubern Merida, A.; Mann, R.M.

2018, Article / Letter to editor (Breast Cancer Research, vol. 20, (2018), article 84)

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

Rodriguez Ruiz, A.; Teuwen, J.J.B.; Vreemann, S.; Bouwman, Ramona W.; Engen, R.E. van; Karssemeijer, N. ; Mann, R.M. ; Gubern Merida, A.; Sechopoulos, I.

2018, Article / Letter to editor (Acta Radiologica (Stockholm: 1921-62), vol. 59, iss. 9, (2018), pp. 1051-1059)

Influence of Risk Category and Screening Round on the Performance of an MR Imaging and Mammography Screening Program in Carriers of the BRCA Mutation and Other Women at Increased Risk

Vreemann, S.; Gubern Merida, A.; Schlooz-Vries, M.S. ; Bult, P. ; Gils, Carla H. van; Hoogerbrugge, N. ; Karssemeijer, N. ; Mann, R.M.

2018, Article / Letter to editor (Radiology, vol. 286, iss. 2, (2018), pp. 443-451)

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

Ehteshami Bejnordi, B.; Mullooly, Maeve; Pfeiffer, Ruth M.; Fan, Shaoqi; Vacek, Pamela M.; Weaver, Donald L.; Ginneken, B. van ; Karssemeijer, N. ; Laak, J.A.W.M. van der ; Sherman, Mark E.

2018, Article / Letter to editor (Modern Pathology, vol. 31, iss. 10, (2018), pp. 1502-1512)

The correlation of background parenchymal enhancement in the contralateral breast with patient and tumor characteristics of MRI-screen detected breast cancers

Vreemann, S.; Gubern Merida, A.; Borelli, C.; Bult, P. ; Karssemeijer, N. ; Mann, R.M.

2018, Article / Letter to editor (PLoS One, vol. 13, iss. 1, (2018), article e0191399)

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

Tellez, D. ; Balkenhol, M.C.; Otte-Holler, I. ; Loo, R.J.M. van de ; Vogels, R.J.; Bult, P. ; Karssemeijer, N. ; Litjens, G.J.; Laak, J.A. van der ; Ciompi, F.

2018, Article / Letter to editor (IEEE Transactions on Medical Imaging, vol. 37, iss. 9, (2018), pp. 2126-2136)

Dedicated computer-aided detection software for automated 3D breast ultrasound; an efficient tool for the radiologist in supplemental screening of women with dense breasts

Zelst, J.C.M. van; Tan, T.; Clauser, Paola; Domingo, Angels; Dorrius, Monique D.; Drieling, Daniel; Karssemeijer, N. ; Mann, R.M.

2018, Article / Letter to editor (European Radiology, vol. 28, iss. 7, (2018), pp. 2996-3006)

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

Rodriguez Ruiz, A.; Gubern Merida, A.; Imhof-Tas, M.W. ; Lardenoije, S.; Wanders, Alexander J.T.; Andersson, Ingvar; Karssemeijer, N. ; Mann, R.M. ; Sechopoulos, I.

2018, Article / Letter to editor (European Radiology, vol. 28, iss. 5, (2018), pp. 1938-1948)

The importance of early detection of calcifications associated with breast cancer in screening

Mordang, J.J.; Gubern Merida, A.; Bria, A.; Tortorella, F.; Mann, R.M. ; Broeders, M.J.M. ; Heeten, G.J. den; Karssemeijer, N.

2018, Article / Letter to editor (Breast Cancer Research and Treatment, vol. 167, iss. 2, (2018), pp. 451-458)

The frequency of missed breast cancers in women participating in a high-risk MRI screening program

Vreemann, S.; Gubern Merida, A.; Lardenoije, S.; Bult, P. ; Karssemeijer, N. ; Pinker, K.; Mann, R.M.

2018, Article / Letter to editor (Breast Cancer Research and Treatment, vol. 169, iss. 2, (2018), pp. 323-331)

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

Zelst, J.C.M. van; Balkenhol, M.C.; Tan, T.; Rutten, M.; Imhof-Tas, M.W. ; Bult, P. ; Karssemeijer, N. ; Mann, R.M.

2017, Article / Letter to editor (Ultrasound in Medicine and Biology, vol. 43, iss. 9, (2017), pp. 1820-1828)

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

Kooi, T.; Karssemeijer, N.

2017, Article / Letter to editor (Journal of Medical Imaging, vol. 4, iss. 4, (2017), article 044501)

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

Mordang, J.J.; Gubern Merida, A.; Bria, A.; Tortorella, F.; Heeten, G.; Karssemeijer, N.

2017, Article / Letter to editor (Medical Physics, vol. 44, iss. 4, (2017), pp. 1390-1401)

Discriminating Solitary Cysts from Soft Tissue Lesions in Mammography using a Pretrained Deep Convolutional Neural Network

Kooi, T.; Ginneken, B. van ; Karssemeijer, N. ; Heeten, A. den

2017, Article / Letter to editor (Medical Physics, vol. 44, iss. 3, (2017), pp. 1017-1027)

Large scale deep learning for computer aided detection of mammographic lesions

Kooi, T.; Litjens, G.J.; Ginneken, B. van ; Gubern Merida, A.; Sanchez, C.I.; Mann, R.M. ; Heeten, A. den; Karssemeijer, N.

2017, Article / Letter to editor (Medical Image Analysis, vol. 35, (2017), pp. 303-312)

Evaluation of a Stratified National Breast Screening Program in the United Kingdom: An Early Model-Based Cost-Effectiveness Analysis

Gray, E.; Donten, A.; Karssemeijer, N. ; Gils, C. van; Evans, D.G.; Astley, S.; Payne, K.

2017, Article / Letter to editor (Value in Health, vol. 20, iss. 8, (2017), pp. 1100-1109)

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

Mus, R.D.M. ; Borelli, C.; Bult, P. ; Weiland, E.; Karssemeijer, N. ; Barentsz, J.O. ; Gubern-Merida, A.; Platel, B.; Mann, R.M.

2017, Article / Letter to editor (European Journal of Radiology, vol. 89, (2017), pp. 90-96)

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

Dalmis, M.U.; Litjens, G.J.; Holland, K.; Setio, A.A.A.; Mann, R.M. ; Karssemeijer, N. ; Gubern Merida, A.

2017, Article / Letter to editor (Medical Physics, vol. 44, iss. 2, (2017), pp. 533-546)

Optimization of volumetric breast density estimation in digital mammograms

Holland, K.; Gubern Merida, A.; Mann, R.M. ; Karssemeijer, N.

2017, Article / Letter to editor (Physics in Medicine and Biology, vol. 62, iss. 9, (2017), pp. 3779-3797)

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

Ehteshami Bejnordi, B.; Zuidhof, G.C.A. ; Balkenhol, M.C.; Hermsen, M. ; Bult, P. ; Ginneken, B. van ; Karssemeijer, N. ; Litjens, G.J.S.; Laak, J.A.W.M. van der

2017, Article / Letter to editor (Journal of Medical Imaging, vol. 4, iss. 4, (2017), article 044504)

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

Holland, K.; Gils, C.H. van; Mann, R.M. ; Karssemeijer, N.

2017, Article / Letter to editor (Breast Cancer Research and Treatment, vol. 162, iss. 3, (2017), pp. 541-548)

The effect of volumetric breast density on the risk of screen-detected and interval breast cancers: a cohort study

Wanders, J.O.; Holland, K.; Karssemeijer, N. ; Peeters, P.H.M.; Veldhuis, W.B.; Mann, R.M. ; Gils, C.H. van

2017, Article / Letter to editor (Breast Cancer Research, vol. 19, iss. 1, (2017), pp. 67)

Volumetric breast density affects performance of digital screening mammography

Wanders, J.O.; Holland, K.; Veldhuis, W.B.; Mann, R.M. ; Pijnappel, R.M.; Peeters, P.H.M.; Gils, C.H. van; Karssemeijer, N.

2017, Article / Letter to editor (Breast Cancer Research and Treatment, vol. 162, iss. 1, (2017), pp. 95-103)

Diagnostic Assessment of Deep Learning Algorithms for Detection of Lymph Node Metastases in Women With Breast Cancer

Ehteshami Bejnordi, B.; Veta, Mitko; Diest, Paul Johannes van; Ginneken, B. van ; Karssemeijer, N. ; Litjens, G.J.S.; Laak, J.A.W.M. van der

2017, Article / Letter to editor (Jama : Journal of the American Medical Association, vol. 318, iss. 22, (2017), pp. 2199-2210)

Influence of breast compression pressure on the performance of population-based mammography screening

Holland, K.; Sechopoulos, I.; Mann, R.M. ; Heeten, G.J. Den; Gils, C.H. van; Karssemeijer, N.

2017, Article / Letter to editor (Breast Cancer Research, vol. 19, (2017), article 126)

Improved cancer detection in automated breast ultrasound by radiologists using Computer Aided Detection

Zelst, J.C. van; Tan, T.; Platel, B.; Jong, M de; Steenbakkers, A.; Mourits, M.; Grivegnee, A.; Borelli, C.; Karssemeijer, N. ; Mann, R.M.

2017, Article / Letter to editor (European Journal of Radiology, vol. 89, (2017), pp. 54-59)

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

Ghafoorian, M.; Karssemeijer, N. ; Heskes, T. ; Bergkamp, M.I.; Wissink, J.; Obels, J.; Keizer, K.; Leeuw, F.E. de ; Ginneken, B. van ; Marchiori, E. ; et al.

sine al.

2017, Article / Letter to editor (Neuroimage. Clinical, vol. 14, (2017), pp. 391-399)

Surveillance of Women with the BRCA1 or BRCA2 Mutation by Using Biannual Automated Breast US, MR Imaging, and Mammography

Zelst, J.C.M. van; Mus, R.D.M. ; Woldringh, G.H. ; Rutten, M.; Bult, P. ; Vreemann, S.; Jong, M de; Karssemeijer, N. ; Hoogerbrugge, N. ; Mann, R.M.

2017, Article / Letter to editor (Radiology, vol. 285, iss. 2, (2017), pp. 376-388)

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

Mertzanidou, T.; Hipwell, J.H.; Reis, S.; Hawkes, D.J.; Ehteshami Bejnordi, B.; Dalmis, M.U.; Vreemann, S.; Platel, B.; Laak, J.A. van der ; Karssemeijer, N. ; et al.

sine al.

2017, Article / Letter to editor (Medical Physics, vol. 44, iss. 3, (2017), pp. 935-948)

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

Vreemann, S.; Rodriguez Ruiz, A.; Nickel, D.; Heacock, L.; Appelman, L.; Zelst, J.C. van; Karssemeijer, N. ; Weiland, E.; Maas, M.C.; Moy, L.; et al.

sine al.

2017, Article / Letter to editor (Investigative Radiology, vol. 52, iss. 10, (2017), pp. 574-582)

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

Ghafoorian, M.; Mehrtash, A.; Kapur, T.; Karssemeijer, N. ; Marchiori, E. ; Pesteie, M.; Guttmann, C.R.G.; Leeuw, F.-E. de; Tempany, C.M.; Ginneken, B. van ; et al.

sine al.

2017, Article in monograph or in proceedings (Descoteaux, M.; Maier-Hein, L.; Franz, A. (ed.), Medical Image Computing and Computer-Assisted Intervention - MICCAI 2017: 20th International Conference, Quebec City, QC, Canada, September 11-13, 2017, Proceedings, Part III, pp. 516-524)

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

Ghafoorian, M.; Karssemeijer, N. ; Heskes, T.M. ; Uden, I.W.M. van ; Sanchez, C.I.; Litjens, G.J.; Leeuw, F.E. de ; Ginneken, B. van ; Marchiori, E. ; Platel, B.

2017, Article / Letter to editor (Scientific Reports, vol. 7, (2017), article 5110)

Reducing false positives of microcalcification detection systems by removal of breast arterial calcifications

Mordang, J.J.; Gubern Merida, A.; Heeten, G.; Karssemeijer, N.

2016, Article / Letter to editor (Medical Physics, vol. 43, iss. 4, (2016), pp. 1676)

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

Ehteshami Bejnordi, B.; Balkenhol, M.; Litjens, G.; Holland, R.; Bult, P. ; Karssemeijer, N. ; Laak, J. ter

2016, Article / Letter to editor (IEEE Transactions on Medical Imaging, vol. 35, iss. 9, (2016), pp. 2141-2150)

Stain Specific Standardization of Whole-Slide Histopathological Images

Bejnordi, B.E.; Litjens, G.; Timofeeva, N; Otte-Holler, I. ; Homeyer, A.; Karssemeijer, N. ; Laak, J.A.W.M. van der

2016, Article / Letter to editor (IEEE Transactions on Medical Imaging, vol. 35, iss. 2, (2016), pp. 404-415)

Consistency of breast density categories in serial screening mammograms: A comparison between automated and human assessment

Holland, K.; Zelst, J. van; Heeten, GJ. den; Imhof-Tas, M.; Mann, R.M. ; Gils, C.H. van; Karssemeijer, N.

2016, Article / Letter to editor (Breast, vol. 29, (2016), pp. 49-54)

The Effect of Supplementary Bone-Suppressed Chest Radiographs on the Assessment of a Variety of Common Pulmonary Abnormalities: Results of an Observer Study

Schalekamp, S.; Karssemeijer, N. ; Cats, A.M.; Hoop, B.J. de ; Geurts, B.H.J.; Berger-Hartog, O.C. ; Ginneken, B. van ; Schaefer-Prokop, C.M.

2016, Article / Letter to editor (Journal of Thoracic Imaging, vol. 31, iss. 2, (2016), pp. 119-125)

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

Kallenberg, M.; Petersen, K.; Nielsen, M.; Ng, A.Y.; Pengfei, D.; Igel, C.; Vachon, C.M.; Holland, K.; Winkel, R.R.; Karssemeijer, N. ; et al.

sine al.

2016, Article / Letter to editor (IEEE Transactions on Medical Imaging, vol. 35, iss. 5, (2016), pp. 1322-1331)

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

Tan, T.; Gubern Merida, A.; Borelli, C.; Manniesing, R.; Zelst, J.C. van; Wang, L.; Zhang, W.; Platel, B.; Mann, R.M. ; Karssemeijer, N.

2016, Article / Letter to editor (Medical Physics, vol. 43, iss. 7, (2016), pp. 4074-4084)

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

Gubern-Merida, A.; Vreemann, S.; Marti, R.; Melendez, J.; Lardenoije, S.; Mann, R.M. ; Karssemeijer, N. ; Platel, B.

2016, Article / Letter to editor (European Journal of Radiology, vol. 85, iss. 2, (2016), pp. 472-479)

Radboud Repository

Browsing by Author "Karssemeijer, N."

Search Repository

Browse

All of Repository