Marleen de Bruijne
Professor
Machine Learning
Universitetsparken 1, 2100 København Ø
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2D-3D shape reconstruction of the distal femur from stereo X-Ray imaging using statistical shape models
Baka, N., Kaptein, B. L., de Bruijne, Marleen, van Walsum, T., Giphart, J. E., Niessen, W. J. & Lelieveldt, B. P. F., 2011, In: Medical Image Analysis. 15, 6, p. 840-850 11 p.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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3D+t/2D+t CTA-XA registration using population-based motion estimates
Baka, N., Metz, C. T., Schultz, C., Neefjes, L., van Geuns, R. J., Lelieveldt, B. P. F., Niessen, W. J., de Bruijne, Marleen & van Walsum, T., 2012, Proceedings, MICCAI-STENT'12: 1st MICCAI-Workshop on Computer Assisted Stenting . Demirci, L. & Radeva, U. (eds.). MICCAI , p. 64-71 8 p.Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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A Computer-based Measure Using Normalized Heights Predicts Vertebral Fracture Independent of BMD in Post-menopausal Women
A. Ghosh, de Bruijne, Marleen, C. Pettersen, M. A. Karsdal, D. J. Leeming, C. Christiansen, P. & Nielsen, Mads, 2008, In: Journal of Bone and Mineral Research. suppl. S, p. S333 1 p.Research output: Contribution to journal › Conference abstract in journal › Research › peer-review
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A Computer-based Measure of Irregularity in Vertebral Alignment is a BMD-independent Predictor of Fracture Risk in Postmenopausal Women
Pettersen, P., de Bruijne, Marleen, Chen, J., He, Q., Christiansen, C. & Tankó, L. B., 2007, In: Osteoporosis International. 18, 11, p. 1525-1530Research output: Contribution to journal › Journal article › Research › peer-review
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A Cross-Center Smoothness Prior for Variational Bayesian Brain Tissue Segmentation
Kouw, W. M., Ørting, S. N., Petersen, Jens, Steenstrup Pedersen, Kim & de Bruijne, Marleen, 1 Jan 2019, Information Processing in Medical Imaging : 26th International Conference, IPMI 2019, Proceedings. Bao, S., Chung, A. C. S., Gee, J. C. & Yushkevich, P. A. (eds.). Springer, p. 360-371 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 11492 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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A Family of Principal Component Analyses for Dealing with Outliers
Iglesias, J. E., de Bruijne, Marleen, Loog, M., Lauze, F. B. & Nielsen, Mads, 2007, Medical Image Computing and Computer-Assisted Intervention - MICCAI 2007: 10th International Conference, Brisbane, Australia, October 29- November 2, 2007, Proceedings, Part II. Ayache, N., Ourselin, S. & Maeder, A. (eds.). Springer, p. 178-185 (Lecture notes in computer science; No. 4792).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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A bottom-up approach for labeling of human airway trees
Lo, P., van Rikxoort, E. M., Goldin, J., Abtin, F., de Bruijne, Marleen & Brown, M., 2011, The Fourth International Workshop on Pulmonary Image Analysis . Beichel, R., de Bruijne, M., Kabus, S., Kiraly, A., Kuhnigk, J-M., McClelland, J., Mori, K., van Rikxoort, E. & Rit, S. (eds.). CreateSpace, p. 23-34 12 p.Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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A computer aided detection system for cerebral microbleeds in brain MRI
Ghafaryasl, B., van der Lijn, F., Poels, M., Vrooman, H., Ikram, M. A., Niessen, W. J., van der Lugt, A., Vernooij, M. & de Bruijne, Marleen, 2012, 2012 9th IEEE International Symposium on Biomedical Imaging: from nano to macro. IEEE, p. 138-141 4 p.Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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A computer-aided diagnosis system for the early and differential diagnosis of neurodegenerative disease
Vrooman, H. A., Jasperse, M. M. S., Koek, M., Achterberg, F. V. D. L. A. H. C., de Bruijne, Marleen, Lugt, A. V. D. & Niessen, W. J., 2011, ECR Conference Proceedings 2011.Research output: Chapter in Book/Report/Conference proceeding › Conference abstract in proceedings › Research › peer-review
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A computer-based measure of irregularity in the alignment of vertebrae in the lumbar spine is a BMD-independent predictor of fracture risk in postmenopausal women
Pettersen, P. C., de Bruijne, Marleen, Chen, J., He, Q., Christiansen, C. & Tankó, L. B., 2007, Abstracts of the 34th European symposium on calcified Tissues. Springer, p. S142 1 p. (Calcified Tissue International; No. Vol. 80 (suppl. 1)).Research output: Chapter in Book/Report/Conference proceeding › Conference abstract in proceedings › Research › peer-review
A genome-wide association study identifies five loci influencing facial morphology in Europeans
Liu, F., van der Lijn, F., Schurmann, C., Zhu, G., Chakravarty, M. M., Hysi, P. G., Wollstein, A., Lao, O., de Bruijne, M., Ikram, M. A., van der Lugt, A., Rivadeneira, F., Uitterlinden, A. G., Hofman, A., Niessen, W. J., Homuth, G., de Zubicaray, G., McMahon, K. L., Thompson, P. M., Daboul, A. & 14 others, , 2012, In: P L o S Genetics. 8, 9, 13 p., e1002932.Research output: Contribution to journal › Journal article › Research › peer-review
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A geometric framework for statistics on trees
Feragen, A., Nielsen, Mads, Hauberg, S., Lo, P. C. P., de Bruijne, Marleen & Lauze, Francois Bernard, 2011, Department of Computer Science, University of Copenhagen. 47 p. (Koebenhavns Universitet. Datalogisk Institut. Rapport; No. 11/02).Research output: Book/Report › Report › Research
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A hierarchical scheme for geodesic anatomical labeling of airway trees
Feragen, A., Petersen, Jens, Owen, M., Lo, P. C. P., Thomsen, L., Wille, M. M. W., Dirksen, A. & de Bruijne, Marleen, 2012, Medical Image Computing and Computer-Assisted Intervention – MICCAI 2012: 15th International Conference, Nice, France, October 1-5, 2012, Proceedings, Part III. Ayache, N., Delingette, H., Golland, P. & Mori, K. (eds.). Springer, p. 147-155 9 p. (Lecture notes in computer science, Vol. 7512).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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A joint 3D UNet-Graph Neural Network-based method for Airway Segmentation from chest CTs
Juarez, A. G., Selvan, Raghav, Saghir, Zaigham & de Bruijne, Marleen, 22 Aug 2019, Machine Learning in Medical Imaging: 10th International Workshop, MLMI 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019, Proceedings. Springer, p. 583-591 (Lecture Notes in Computer Science, Vol. LNCS 11861).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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A longitudinal follow-up of COPD disease progression in a large cohort of smokers screened for early lung cancer: CBQ study
Ashraf, H., Edula, G., de Bruijne, Marleen, Nielsen, Mads, Dahlbäck, A. D. M. & Pedersen, J. H., 2009, In: American Journal of Respiratory and Critical Care Medicine. p. A1492 1 p.Research output: Contribution to journal › Conference abstract in journal › Research › peer-review
A method of deriving a quantitative measure of a degree of calcification of an aorta
de Bruijne, Marleen, Nielsen, M., Christiansen, C., Conrad-Hansen, L. A. & Lauze, F. B., 2006, Patent No. WO/2006/128729Research output: Patent
A novel computer-based quantitative measurement of vertebral deformity in postmenopausal women: Implications for diagnosis and monitoring
de Bruijne, Marleen, Pettersen, P. C., Lund, M. T., Alexandersen, P., Tankó, L. B., Nielsen, M. & Christiansen, C., 2006, Abstracts of the 28th Annual Meeting of the American Society for Bone and Mineral Research. ASMBRResearch output: Chapter in Book/Report/Conference proceeding › Conference abstract in proceedings › Research › peer-review
A pattern classification approach to aorta calcium scoring in radiographs
de Bruijne, Marleen, 2005, Computer Vision for Biomedical Image Applications: ICCV workshop: Computer Vision for Biomedical Image Applications: Current Techniques and Future Trends. <Forlag uden navn>, p. 170-177 (Lecture notes in computer science, Vol. 3765/2005).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
A pixelwise inpainting-based refinement scheme for quantizing calcification in the lumbar aorta on 2D lateral x-ray images
Conrad-Hansen, L., de Bruijne, Marleen, Lauze, F., Tankó, L. B. & Nielsen, M., 2006, Medical Imaging: Image Processing. Pluim, J. P. W. & Reinhardt, J. M. (eds.). (Proceedings of SPIE; No. 6144).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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A texton-based approach for the classification of lung parenchyma in CT images
Gangeh, M. J., Sørensen, L., Shaker, S. B., Kamel, M. S., de Bruijne, Marleen & Loog, M., 2010, Medical Image Computing and Computer-Assisted Intervention - MICCAI 2010: 13th International Conference, Beijing, China, September 20-24, 2010, Proceedings, Part III. Jiang, T., Navab, N., Pluim, J. P. W. & Viergever, M. A. (eds.). Springer, Vol. Part III. p. 595-602 8 p. (Lecture notes in computer science; No. 6363).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › 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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APIR-Net: Autocalibrated Parallel Imaging Reconstruction Using a Neural Network
Zhang, C., Dubost, F., de Bruijne, Marleen, Klein, S. & Poot, D. H. J., 1 Jan 2019, Machine Learning for Medical Image Reconstruction : Second International Workshop, MLMIR 2019 Held in Conjunction with MICCAI 2019 Shenzhen, China, October 17, 2019, Proceedings. Knoll, F., Maier, A., Rueckert, D. & Ye, J. C. (eds.). Springer VS, p. 36-46 11 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 11905 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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Active shape model based segmentation of abdominal aortic aneurysms in CTA images
de Bruijne, Marleen, van Ginneken, B., Niessen, W., Maintz, J. & Viergever, M., 2002, MEDICAL IMAGING 2002: IMAGE PROCESSING, VOL 1-3. Vol. 4684. p. 463-474Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
Adapting Active Shape Models for 3D Segmentation of Tubular Structures in Medical Images
de Bruijne, Marleen, van Ginneken, B., Viergever, M. A. & Niessen, W. J., 2003, Information Processing in Medical Imaging: 18th International Conference, IPMI 2003. Ambleside, UK, July 20- 25, 2003. Proceedings. <Forlag uden navn>, p. 136-147 (Lecture notes in computer science, Vol. 2732/2003).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › 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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Air trapping in cystic fibrosis (CF) evaluated using ultra low dose computed tomography (CT): implications for sample size in clinical studies
Loeve, M., Lequin, M. H., de Bruijne, Marleen, Hartmann, I. J., Hop, W. C. & Tiddens, H. A. W. M., 2008.Research output: Contribution to conference › Conference abstract for conference › Research › peer-review
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Airway Tree Extraction with Locally Optimal Paths
Lo, P. C. P., Sporring, Jon, Pedersen, J. J. H. & de Bruijne, Marleen, 2009, MICCAI 2009. p. 51-58 8 p.Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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Airway distensibility in chronic obstructive pulmonary disease – evaluation by CT airway segmentation and lung density measurement based on the Danish lung cancer screening trial
M. W. Wille, M., Petersen, Jens, Dirksen, A., Pedersen, J. J. H. & de Bruijne, Marleen, 2013, In: American Journal of Respiratory and Critical Care Medicine. 187, p. A2871 1 p.Research output: Contribution to journal › Conference abstract in journal › Research › peer-review
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Airway tapering: An objective image biomarker for bronchiectasis
Kuo, W., Perez-Rovira, A., Tiddens, H. & de Bruijne, Marleen, 2020, In: European Radiology. 30, 5, p. 2703-2711Research output: Contribution to journal › Journal article › Research › peer-review
An End-to-end Approach to Semantic Segmentation with 3D CNN and Posterior-CRF in Medical Images
Chen, S. & de Bruijne, Marleen, 8 Nov 2018. 4 p.Research output: Contribution to conference › Paper › Research › peer-review
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An airway tree-shape model for geodesic airway branch labeling
Feragen, A., Lo, P. C. P., Gorbunova, V., Nielsen, Mads, Dirksen, A., Reinhardt, J. M., Lauze, Francois Bernard & de Bruijne, Marleen, 2011, MFCA 2011: 3rd MICCAI Workshop on Mathematical Foundations of Computational Anatomy. Pennec, X., Joshi, S. & Nielsen, M. (eds.). p. 123-134 12 p.Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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An automatic system for segmentation, matching, anatomical labeling and measurement of airways from CT images
Petersen, Jens, Feragen, A., Owen, M., Lo, P., Wille, M. M. W., Thomsen, L. H., Dirksen, A. & de Bruijne, Marleen, 2013. 1 p.Research output: Contribution to conference › Poster › Research › peer-review
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An end-to-end approach to segmentation in medical images with CNN and posterior-CRF
Chen, S., Sedghi Gamechi, Z., Dubost, F., van Tulder, G. & de Bruijne, Marleen, Feb 2022, In: Medical Image Analysis. 76, p. 1-12 102311.Research output: Contribution to journal › Journal article › Research › peer-review
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Aorta and pulmonary artery segmentation using optimal surface graph cuts in non-contrast CT
Sedghi Gamechi, Z., Arias-Lorza, A. M., Pedersen, J. H. & de Bruijne, Marleen, 2018, Medical Imaging 2018: Image Processing. SPIE - International Society for Optical Engineering, 7 p. 105742D. (Proceedings of SPIE International Symposium on Medical Imaging, Vol. 10574).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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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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Asymmetric similarity-weighted ensembles for image segmentation
Cheplygina, V., Van Opbroek, A., Ikram, M. A., Vernooij, M. W. & de Bruijne, Marleen, 2016, 2016 IEEE International Symposium on Biomedical Imaging: from Nano to Macro. IEEE, p. 273-277 5 p.Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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Atherosclerotic plaque component segmentation in combined carotid MRI and CTA data incorporating class label uncertainty
van Engelen, A., Niessen, W. J., Klein, S., Groen, H. C., Verhagen, H. J. M., Wentzel, J. J., van der Lugt, A. & de Bruijne, Marleen, 2014, In: PLoS ONE. 9, 4, 14 p., e94840.Research output: Contribution to journal › Journal article › Research › peer-review
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Automated 3D segmentation and diameter measurement of the thoracic aorta on non-contrast enhanced CT
Sedghi Gamechi, Z., Bons, L. R., Giordano, M., Bos, D., Budde, R. P. J., Kofoed, Klaus Fuglsang, Pedersen, J. H., Roos-Hesselink, J. W. & de Bruijne, Marleen, 23 Jan 2019, In: European Radiology. 29, 9, p. 4613-4623Research 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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Automated Quantification of the Morphological Atherosclerotic Calcification Distribution on X-Rays Is a Strong Predictor of Mortality in Postmenopausal Women
Christiansen, C., Karsdal, M., Lauze, Francois Bernard, Dam, E., Ganz, Melanie, de Bruijne, Marleen, Sørensen, M., Barascuk, N. & Nielsen, Mads, 2008, In: Arteriosclerosis, Thrombosis, and Vascular Biology. 6, p. e48-e48 1 p.Research output: Contribution to journal › Conference abstract in journal › Research › peer-review
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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
Automated Segmentation of Abdominal Aortic Aneurysms in Multi-spectral MR Images
de Bruijne, Marleen, van Ginneken, B., Bartels, L. W., van der Laan, M. J., Blankensteijn, J. D., Niessen, W. J. & Viergever, M. A., 2003, Medical Image Computing and Computer-Assisted Intervention - MICCAI. <Forlag uden navn>, p. 538-545 (Lecture notes in computer science, Vol. 2879/2003).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 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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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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Automated measurement of diagnostic angles for hip dysplasia
de Raedt, S., Mechlenburg, I. B., Stilling, M., Mikkelsen, L. R., Søballe, K. & de Bruijne, Marleen, 2013, Medical Imaging 2013: Computer-Aided Diagnosis. Novak, C. L. & Aylward, S. (eds.). SPIE - International Society for Optical Engineering, 10 p. 867009. (Proceedings of S P I E - International Society for Optical Engineering, Vol. 8670).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › 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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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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