Marleen de Bruijne
Professor
Machine Learning
Universitetsparken 1, 2100 København Ø
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Automated Segmentation and Volume Measurement of Intracranial Internal Carotid Artery Calcification at Noncontrast CT
Bortsova, G., Bos, D., Dubost, F., Vernooij, M. W., Ikram, M. K., van Tulder, G. & de Bruijne, Marleen, Sep 2021, In: Radiology: Artificial Intelligence. 3, 5, 10 p., e200226.Research output: Contribution to journal › Journal article › Research › peer-review
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Adversarial attack vulnerability of medical image analysis systems: Unexplored factors
Bortsova, G., González-Gonzalo, C., Wetstein, S. C., Dubost, F., Katramados, I., Hogeweg, L., Liefers, B., van Ginneken, B., Pluim, J. P. W., Veta, M., Sánchez, C. I. & de Bruijne, Marleen, 2021, In: Medical Image Analysis. 73, 14 p., 102141.Research output: Contribution to journal › Journal article › Research › peer-review
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Uncertainty-Based Segmentation of Myocardial Infarction Areas on Cardiac MR Images
Camarasa, R., Faure, A., Crozier, T., Bos, D. & de Bruijne, Marleen, 2021, Statistical Atlases and Computational Models of the Heart. MandMs and EMIDEC Challenges - 11th International Workshop, STACOM 2020, Held in Conjunction with MICCAI 2020, Revised Selected Papers. Puyol Anton, E., Pop, M., Sermesant, M., Campello, V., Lalande, A., Lekadir, K., Suinesiaputra, A., Camara, O. & Young, A. (eds.). Springer, p. 385-391 7 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 12592 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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A Quantitative Comparison of Epistemic Uncertainty Maps Applied to Multi-Class Segmentation
Camarasa, R., Bos, D., Hendrikse, J., Nederkoorn, P., Kooi, M. E., Lugt, A. V. D. & de Bruijne, Marleen, 22 Sep 2021, In: The Journal of Machine Learning for Biomedical Imaging. 2021, p. 1-39 013.Research output: Contribution to journal › Journal article › Research › peer-review
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Crowdsourcing airway annotations in chest computed tomography images
Cheplygina, V., Perez-Rovira, A., Kuo, W., Tiddens, H. A. W. M. & de Bruijne, Marleen, 2021, In: PLoS ONE. 16, e0249580.Research output: Contribution to journal › Journal article › Research › peer-review
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Creating a training set for artificial intelligence from initial segmentations of airways
Dudurych, I., Garcia-Uceda, A., Saghir, Zaigham, Tiddens, H. A. W. M., Vliegenthart, R. & de Bruijne, Marleen, 2021, In: European radiology experimental. 5, 1, 7 p., 54.Research output: Contribution to journal › Journal article › Research › peer-review
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Preface
Ernst, F., Heinrich, M., Lellmann, J., Schlaefer, A., Dou, Q. & de Bruijne, Marleen, 2021, e Proceedings of the Fourth International Conference on Medical Imaging with Deep Learning – MIDL 2021. PMLR, p. 1-4 (Proceedings of Machine Learning Research, Vol. 143).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research
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Assessment of fully automatic segmentation of pulmonary artery and aorta on non-contrast CT with optimal surface graph cuts
Gamechi, Z. S., Arias-Lorza, A. M., Saghir, Z., Bos, D. & de Bruijne, Marleen, 2021, In: Medical Physics. 48, 12, p. 7837-7849Research output: Contribution to journal › Journal article › Research › peer-review
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Automatic airway segmentation from computed tomography using robust and efficient 3-D convolutional neural networks
Garcia-uceda, A., Selvan, Raghav, Saghir, Zaigham, Tiddens, H. A. W. M. & de Bruijne, Marleen, 2021, In: Scientific Reports. 11, 1, 15 p., 16001.Research output: Contribution to journal › Journal article › Research › peer-review
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Chest MRI to diagnose early diaphragmatic weakness in Pompe disease
Harlaar, L., Ciet, P., van Tulder, G., Pittaro, A., van Kooten, H. A., van der Beek, N. A. M. E., Brusse, E., Wielopolski, P. A., de Bruijne, Marleen, van der Ploeg, A. T., Tiddens, H. A. W. M. & van Doorn, P. A., 2021, In: Orphanet Journal of Rare Diseases. 16, 1, p. 1-12 21.Research output: Contribution to journal › Journal article › Research › peer-review
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Developing and validating COVID-19 adverse outcome risk prediction models from a bi-national European cohort of 5594 patients
Jimenez-Solem, E., Petersen, T. S., Hansen, C., Hansen, C., Lioma, C., Igel, C., Boomsma, W., Krause, O., Lorenzen, S., Selvan, R., Petersen, J., Nyeland, M. E., Ankarfeldt, M. Z., Virenfeldt, G. M., Winther-Jensen, M., Linneberg, A., Ghazi, M. M., Detlefsen, N., Lauritzen, A. D., Smith, A. G. & 15 others, , 2021, In: Scientific Reports. 11, 1, 12 p., 3246.Research output: Contribution to journal › Journal article › Research › peer-review
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Intracranial arteriosclerosis is related to cerebral small vessel disease: a prospective cohort study
Vinke, E. J., Yilmaz, P., van der Toorn, J. E., Fakhry, R., Frenzen, K., Dubost, F., Licher, S., de Bruijne, Marleen, Kavousi, M., Ikram, M. A., Vernooij, M. W. & Bos, D., 2021, In: Neurobiology of Aging. 105, p. 16-24Research output: Contribution to journal › Journal article › Research › peer-review
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Learning from Imperfect Data: Weak Labels, Shifting Domains, and Small Datasets in Medical Imaging
de Bruijne, Marleen, 2021, Bildverarbeitung für die Medizin 2021: Proceedings, German Workshop on Medical Image Computing, Regensburg, March 7-9, 2021. Springer, p. 1 1 p.Research output: Chapter in Book/Report/Conference proceeding › Conference abstract in proceedings › Research
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Preface (vols 1-8)
de Bruijne, Marleen, Cattin, P. C., Cotin, S., Padoy, N., Speidel, S., Zheng, Y. & Essert, C., 2021, Medical Image Computing and Computer Assisted Intervention – MICCAI 2021: 24th International Conference, Strasbourg, France, September 27 – October 1, 2021, Proceedings, Part VII. Springer, Vol. 12905 LNCS. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research
ID: 545222
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Evaluation of registration methods on thoracic CT: the EMPIRE10 challenge
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Atherosclerotic plaque component segmentation in combined carotid MRI and CTA data incorporating class label uncertainty
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Distribution, size, shape, growth potential and extent of abdominal aortic calcified deposits predict mortality in postmenopausal women
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