Marleen de Bruijne
Professor
Machine Learning
Universitetsparken 1, 2100 København Ø
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GP-Unet: Lesion detection from weak labels with a 3D regression network
Dubost, F., Bortsova, G., Adams, H., Ikram, A., Niessen, W. J., Vernooij, M. & de Bruijne, Marleen, 2017, Medical Image Computing and Computer-Assisted Intervention − MICCAI 2017: 20th International Conference, Quebec City, QC, Canada, September 11-13, 2017, Proceedings, Part III. Descoteaux, M., Maier-Hein, L., Franz, A., Jannin, P., Collins, D. L. & Duschesne, S. (eds.). Springer, p. 214-221 8 p. (Lecture notes in computer science, Vol. 10435).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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Enlarged perivascular spaces in brain MRI: Automated quantification in four regions
Dubost, F., Yilmaz, P., Adams, H., Bortsova, G., Ikram, M. A., Niessen, W., Vernooij, M. & de Bruijne, Marleen, 2019, In: NeuroImage. 185, p. 534-544Research output: Contribution to journal › Journal article › Research › peer-review
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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
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Automated Quantification of Enlarged Perivascular Spaces in Clinical Brain MRI Across Sites
Dubost, F., Dünnwald, M., Huff, D., Scheumann, V., Schreiber, F., Vernooij, M., Niessen, W., Skalej, M., Schreiber, S., Oeltze-Jafra, S. & de Bruijne, Marleen, 2019, OR 2.0 Context-Aware Operating Theaters and Machine Learning in Clinical Neuroimaging - 2nd International Workshop, OR 2.0 2019, and 2nd International Workshop, MLCN 2019, Held in Conjunction with MICCAI 2019, Proceedings. Zhou, L., Sarikaya, D., Kia, S. M., Speidel, S., Malpani, A., Hashimoto, D., Habes, M., Löfstedt, T., Ritter, K. & Wang, H. (eds.). Springer VS, p. 103-111 9 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 11796 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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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
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3D regression neural network for the quantification of enlarged perivascular spaces in brain MRI
Dubost, F., Adams, H., Bortsova, G., Ikram, M. A., Niessen, W., Vernooij, M. & de Bruijne, Marleen, Jan 2019, In: Medical Image Analysis. 51, p. 89-100Research output: Contribution to journal › Journal article › Research › peer-review
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Hydranet: Data augmentation for regression neural networks
Dubost, F., Bortsova, G., Adams, H., Ikram, M. A., Niessen, W., Vernooij, M. & de Bruijne, Marleen, 1 Jan 2019, Medical Image Computing and Computer Assisted Intervention – MICCAI 2019 - 22nd International Conference, Proceedings. Shen, D., Yap, P-T., Liu, T., Peters, T. M., Khan, A., Staib, L. H., Essert, C. & Zhou, S. (eds.). Springer VS, p. 438-446 9 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 11767 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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Weakly supervised object detection with 2D and 3D regression neural networks
Dubost, F., Adams, H., Yilmaz, P., Bortsova, G., Tulder, G. V., Ikram, M. A., Niessen, W., Vernooij, M. W. & de Bruijne, Marleen, Oct 2020, In: Medical Image Analysis. 65, 22 p., 101767.Research output: Contribution to journal › Journal article › Research › peer-review
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Reproducibility of a combined artificial intelligence and optimal-surface graph-cut method to automate bronchial parameter extraction
Dudurych, I., Garcia-Uceda, A., Petersen, Jens, Du, Y., Vliegenthart, R. & de Bruijne, Marleen, 2023, In: European Radiology. 33, p. 6718–6725Research 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
ID: 545222
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Evaluation of registration methods on thoracic CT: the EMPIRE10 challenge
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2336
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Atherosclerotic plaque component segmentation in combined carotid MRI and CTA data incorporating class label uncertainty
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2145
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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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