Marleen de Bruijne
Professor
Image Analysis, Computational Modelling and Geometry
Universitetsparken 1
2100 København Ø
- 2020
- Published
Automated Estimation of the Spinal Curvature via Spine Centerline Extraction with Ensembles of Cascaded Neural Networks
Dubost, F., Collery, B., Renaudier, A., Roc, A., Posocco, N., Niessen, W. & de Bruijne, Marleen, 2020, Computational Methods and Clinical Applications for Spine Imaging: 6th International Workshop and Challenge, CSI 2019, Proceedings. Cai, Y., Wang, L., Audette, M., Zheng, G. & Li, S. (eds.). Springer VS, p. 88-94 7 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 11963 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- Published
Chronic Obstructive Pulmonary Disease Quantification Using CT Texture Analysis and Densitometry: Results From the Danish Lung Cancer Screening Trial
Sørensen, L., Nielsen, Mads, Petersen, Jens, Pedersen, J. H., Dirksen, A. & de Bruijne, Marleen, 2020, In: American Journal of Roentgenology. 214, 6, p. 1269-1279Research output: Contribution to journal › Journal article › Research › peer-review
- Published
Classification of Volumetric Images Using Multi-Instance Learning and Extreme Value Theorem
Tennakoon, R., Bortsova, G., Orting, S., Gostar, A. K., Wille, M. M. W., Saghir, Zaigham, Hoseinnezhad, R., de Bruijne, Marleen & Bab-Hadiashar, A., 2020, In: IEEE Transactions on Medical Imaging. 39, 4, p. 854-865Research output: Contribution to journal › Journal article › Research › peer-review
- Published
Graph Refinement based Airway Extraction using Mean-Field Networks and Graph Neural Networks
Selvan, Raghav, Kipf, T., Welling, M., Juarez, A. G., Pedersen, J. H., Petersen, Jens & de Bruijne, Marleen, 2020, In: Medical Image Analysis. 64, 12 p., 101751.Research output: Contribution to journal › Journal article › Research › peer-review
- Published
Growth of the thoracic aorta in the smoking population: The Danish Lung Cancer Screening Trial
Bons, L. R., Sedghi Gamechi, Z., Thijssen, C. G. E., Kofoed, Klaus Fuglsang, Pedersen, J. H., Saghir, Zaigham, Takkenberg, J. J. M., Kardys, I., Budde, R. P. J., de Bruijne, Marleen & Roos-Hesselink, J. W., 2020, In: International Journal of Cardiology. 299, p. 276-281Research output: Contribution to journal › Journal article › Research › peer-review
- Published
Learning to quantify emphysema extent: What labels do we need?
Orting, S. N., Petersen, Jens, Thomsen, L. H., Winkler Wille, M. M. & de Bruijne, Marleen, 2020, In: IEEE Journal of Biomedical and Health Informatics. 24, 4, p. 1149 -1159Research output: Contribution to journal › Journal article › Research › peer-review
- Published
Multi-atlas image registration of clinical data with automated quality assessment using ventricle segmentation
Dubost, F., de Bruijne, Marleen, Nardin, M., Dalca, A. V., Donahue, K. L., Giese, A., Etherton, M. R., Wu, O., Groot, M. D., Niessen, W., Vernooij, M., Rost, N. S. & Schirmer, M. D., 2020, In: Medical Image Analysis. 63, 14 p., 101698.Research output: Contribution to journal › Journal article › Research › peer-review
- Published
Preface
Arbel, T., Ayed, I. B., de Bruijne, Marleen, Descoteaux, M., Lombaert, H. & Pal, C., 2020, Proceedings of the Third Conference on Medical Imaging with Deep Learning – MIDL 2020. PMLR, Vol. 121. p. 1-5 (Proceedings of Machine Learning Research, Vol. 121).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research
- Published
Quantitative Comparison of Monte-Carlo Dropout Uncertainty Measures for Multi-class Segmentation
Camarasa, R., Bos, D., Hendrikse, J., Nederkoorn, P., Kooi, E., van der Lugt, A. & de Bruijne, Marleen, 2020, Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Graphs in Biomedical Image Analysis - 2nd International Workshop, UNSURE 2020, and 3rd International Workshop, GRAIL 2020, Held in Conjunction with MICCAI 2020, Proceedings. Sudre, C. H., Fehri, H., Arbel, T., Baumgartner, C. F., Dalca, A., Tanno, R., Van Leemput, K., Wells, W. M., Sotiras, A., Papiez, B., Ferrante, E. & Parisot, S. (eds.). Springer, p. 32-41 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 12443 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- Published
Region-of-interest guided supervoxel inpainting for self-supervision
Kayal, S., Chen, S. & de Bruijne, Marleen, 2020, Medical Image Computing and Computer Assisted Intervention – MICCAI 2020 - 23rd International Conference, Proceedings. Martel, A. L., Abolmaesumi, P., Stoyanov, D., Mateus, D., Zuluaga, M. A., Zhou, S. K., Racoceanu, D. & Joskowicz, L. (eds.). Springer VS, p. 500-509 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 12261 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
ID: 545222
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Evaluation of registration methods on thoracic CT: the EMPIRE10 challenge
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2355
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Atherosclerotic plaque component segmentation in combined carotid MRI and CTA data incorporating class label uncertainty
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2172
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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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Published