Marleen de Bruijne
Professor
Image Analysis, Computational Modelling and Geometry
Universitetsparken 1
2100 København Ø
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Crowdsourced emphysema assessment
Ørting, S. N., Cheplygina, V., Petersen, Jens, Thomsen, L. H., Wille, M. M. W. & de Bruijne, Marleen, 2017, Intravascular Imaging and Computer Assisted Stenting, and Large-Scale Annotation of Biomedical Data and Expert Label Synthesis: 6th Joint International Workshops, CVII-STENT 2017 and Second International Workshop, LABELS 2017, Held in Conjunction with MICCAI 2017, Québec City, QC, Canada, September 10–14, 2017, Proceedings. Cardoso, M. J., Arbel, T., Lee, S-L., Cheplygina, V., Balocco, S., Mateus, D., Zahnd, G., Maier-Hein, L., Dermirci, S., Granger, E., Duong, L., Carbonneau, M-A., Albarquoni, S. & Carneiro, G. (eds.). Springer, p. 126-135 10 p. (Lecture notes in computer science, Vol. 10552).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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Quantifying emphysema extent from weakly labeled CT scans of the lungs using label proportions learning
Ørting, S. N., Petersen, Jens, Wille, M., Thomsen, L. & de Bruijne, Marleen, 2016, The Sixth International Workshop on Pulmonary Image Analysis. Beichel, R. R., Farahani, K., Jacobs, C., Kabus, S., Kiraly, A. P., Kuhnigk, J-M., McClelland, J. R., Mori, K., Petersen, J. & S. R. (eds.). CreateSpace Independent Publishing Platform , p. 31-42 11 p.Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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Automated brain structure segmentation based on atlas registration and appearance models
van der Lijn, F., de Bruijne, Marleen, Klein, S., den Heijer, T., Hoogendam, Y. Y., van der Lugt, A., Breteler, M. M. B. & Niessen, W. J., 2012, In: IEEE Transactions on Medical Imaging. 31, 2, p. 276-286 11 p.Research output: Contribution to journal › Journal article › Research › peer-review
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Automated measurement of local white matter lesion volume
van der Lijn, F., Verhaaren, B. F. J., Ikram, M. A., Klein, S., de Bruijne, Marleen, Vrooman, H. A., Vernooij, M. W., Hammers, A., Rueckert, D., van der Lugt, A., Breteler, M. M. B. & Niessen, W. J., 2012, In: NeuroImage. 59, 4, p. 3901-3908 8 p.Research output: Contribution to journal › Journal article › Research › peer-review
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Cerebellum segmentation in MRI using atlas registration and local multi-scale image descriptors
van der Lijn, F., de Bruijne, Marleen, Hoogendam, Y. Y., Klein, S., Hameeteman, R., Breteler, M. & Niessen, W., 2009, IEEE International Symposium on Biomedical Imaging (ISBI'09): From Nano to Macro. p. 221-224 4 p. (Uden navn).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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Automated lesion detection by regressing intensity-based distance with a neural network
van Wijnen, K. M. H., Dubost, F., Yilmaz, P., Ikram, M. A., Niessen, W. J., Adams, H., Vernooij, M. W. & 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. 234-242 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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Learning Cross-Modality Representations from Multi-Modal Images
van Tulder, G. & de Bruijne, Marleen, 2019, In: IEEE Transactions on Medical Imaging. 38, 2, p. 638-648Research output: Contribution to journal › Journal article › Research › peer-review
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Learning features for tissue classification with the classification restricted Boltzmann machine
van Tulder, G. & de Bruijne, Marleen, 2014, Medical Computer Vision: Algorithms for Big Data: International Workshop, MCV 2014, Held in Conjunction with MICCAI 2014, Cambridge, MA, USA, September 18, 2014, Revised Selected Papers. Menze, B., Langs, G., Montillo, A., Kelm, M., Müller, H., Zhang, S., Cai, W. T. & Metaxas, D. (eds.). Springer, p. 47-58 12 p. (Lecture notes in computer science).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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Unpaired, unsupervised domain adaptation assumes your domains are already similar
van Tulder, G. & de Bruijne, Marleen, 2023, In: Medical Image Analysis. 87, 17 p., 102825.Research output: Contribution to journal › Journal article › Research › peer-review
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Why does synthesized data improve multi-sequence classification?
van Tulder, G. & de Bruijne, Marleen, 2015, Medical image computing and computer assisted interventions - MICCAI 2015: 18th International Conference, Munich, Germany, October 5-9, 2015, Proceedings, Part I. Springer, p. 531-538 8 p. (Lecture notes in computer science, Vol. 9349).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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Combining generative and discriminative representation learning for lung CT analysis with convolutional restricted Boltzmann machines
van Tulder, G. & de Bruijne, Marleen, 2016, In: IEEE Transactions on Medical Imaging. 35, 5, p. 1262-1272 11 p.Research output: Contribution to journal › Journal article › Research › peer-review
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Integrating local voxel classification and global shape models for medical image segmentation
van Rikxoort, E. M., de Bruijne, Marleen & van Ginneken, B., 2008, Medical Imaging 2008: Image Processing, Conference Proceedings. Reinhardt, J. M. & Pluim, J. P. W. (eds.). SPIE - International Society for Optical Engineering, p. Article 69144J 6 p. (Proceedings of SPIE; No. 6914).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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Transfer Learning for Image Segmentation by Combining Image Weighting and Kernel Learning
van Opbroek, A., Achterberg, H. C., Vernooij, M. W. & de Bruijne, Marleen, 2019, In: IEEE Transactions on Medical Imaging. 38, 1, p. 213-224 8419778.Research output: Contribution to journal › Journal article › Research › peer-review
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Automated brain-tissue segmentation by multi-feature SVM classification
van Opbroek, A., van der Lijn, F. & de Bruijne, Marleen, 2013, The MICCAI Grand Challenge on MR Brain Image Segmentation (MRBrainS13). 8 p. (The MIDAS Journal).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research
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Feature-space transformation improves supervised segmentation across scanners
van Opbroek, A., Achterberg, H. C. & de Bruijne, Marleen, 2015, Machine learning meets medical imaging: First International Workshop, MLMMI 2015, Held in Conjunction with ICML 2015, Lille, France, July 11, 2015, Revised Selected Papers. Springer, p. 85-93 9 p. (Lecture notes in computer science, Vol. 9487).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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Weighting training images by maximizing distribution similarity for supervised segmentation across scanners
van Opbroek, A., Vernooij, M. W., Ikram, M. A. & de Bruijne, Marleen, 2015, In: Medical Image Analysis. 24, 1, p. 245-254 10 p.Research output: Contribution to journal › Journal article › Research › peer-review
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Transfer learning improves supervised image segmentation across imaging protocols
van Opbroek, A., Ikram, M. A., Vernooij, M. W. & de Bruijne, Marleen, 2015, In: IEEE Transactions on Medical Imaging. 34, 5, p. 1018-1030 13 p.Research output: Contribution to journal › Journal article › Research › peer-review
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A transfer-learning approach to image segmentation across scanners by maximizing distribution similarity
van Opbroek, A., Ikram, M. A., Vernooij, M. W. & de Bruijne, Marleen, 2013, Machine Learning in Medical Imaging: 4th International Workshop, MLMI 2013, held in conjunction with MICCAI 2013, Nagoya, Japan, September 22, 2013. Proceedings. Wu, G., Zhang, D., Shen, D., Yan, P., Suzuki, K. & Wang, F. (eds.). Springer, p. 49-56 8 p. (Lecture notes in computer science, Vol. 8184).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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Transfer learning by feature-space transformation: A method for Hippocampus segmentation across scanners
van Opbroek, A., Achterberg, H. C., Vernooij, M. W., Arfan Ikram, M. & de Bruijne, Marleen, 2018, In: NeuroImage: Clinical. 20, p. 466-475 10 p.Research output: Contribution to journal › Journal article › Research › peer-review
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Supervised image segmentation across scanner protocols: a transfer learning approach
van Opbroek, A., Ikram, M. A., Vernooij, M. W. & de Bruijne, Marleen, 2012, Machine Learning in Medical Imaging: Third International Workshop, MLMI 2012, Held in Conjunction with MICCAI 2012, Nice, France, October 1, 2012, Revised Selected Papers. Wang, F., Shen, D., Yan, P. & Suzuki, K. (eds.). Springer, p. 160-167 8 p. (Lecture notes in computer science, Vol. 7588).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
Interactive shape models
van Ginneken, B., de Bruijne, Marleen, Loog, M. & Viergever, M. A., 2003, Proceedings of SPIE. p. 1206-1216 (Medical Imaging 2003: Image Processing, Vol. 5032).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
Evaluating classifiers for atherosclerotic plaque component segmentation in MRI
van Engelen, A., de Bruijne, Marleen, Schneider, T., van Dijk, A. C., Kooi, M. E., Hendrikse, J., Nederveen, A., Niessen, W. & Botnar, R. M., 2017, Medical Image Understanding and Analysis: 21st Annual Conference, MIUA 2017, Edinburgh, UK, July 11–13, 2017, Proceedings. Hernández, M. V. & González-Castro, V. (eds.). Springer, Vol. 723. p. 156-168 13 p. (Communications in Computer and Information Science, Vol. 723).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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Plaque characterization in ex vivo MRI evaluated by dense 3D correspondence with histology
van Engelen, A., de Bruijne, Marleen, Klein, S., Groen, H., Wentzel, J., van der Lugt, A. & Niessen, W., 2011.Research output: Contribution to conference › Conference abstract for conference › Research
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Plaque characterization in ex vivo MRI evaluated by dense 3D correspondence with histology
van Engelen, A., de Bruijne, Marleen, Klein, S., Verhagen, H., Groen, H., Wentzel, J., van der Lugt, A. & Niessen, W., 2011, Medical Imaging 2011: computer-aided diagnosis. Summers, R. M. & van Ginneken, B. (eds.). SPIE - International Society for Optical Engineering, Vol. Part One. 11 p. 796329. (Progress in Biomedical Optics and Imaging; No. 32, Vol. 12).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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Three-dimensional carotid ultrasound plaque texture predicts vascular events
van Engelen, A., Wannarong, T., Parraga, G., Niessen, W. J., Fenster, A., Spence, J. D. & de Bruijne, Marleen, 2014, In: Stroke. 45, p. 2695-2701 7 p.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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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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