Marleen de Bruijne
Professor
Machine Learning
Universitetsparken 1, 2100 København Ø
- Published
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
- Published
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
- Published
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
- Published
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
- Published
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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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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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
- Published
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
- Published
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
- Published
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
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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