Marleen de Bruijne

Leveraging Ellipsoid Bounding Shapes and Fast R-CNN for Enlarged Perivascular Spaces Detection and Segmentation

Zabihi, M., Tangwiriyasakul, C., Ingala, S., Lorenzini, L., Camarasa, R., Barkhof, F., de Bruijne, Marleen, Cardoso, M. J. & Sudre, C. H., 2024, Machine Learning in Medical Imaging - 14th International Workshop, MLMI 2023, Held in Conjunction with MICCAI 2023, Proceedings. Cao, X., Ouyang, X., Xu, X., Rekik, I. & Cui, Z. (eds.). Springer, p. 325-334 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 14349 LNCS).

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Graph cut-based segmentation

Petersen, Jens, Oguz, I. & de Bruijne, Marleen, 2023, Medical Image Analysis. Academic Press, p. 247-273

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Preface: Information Processing in Medical Imaging (IPMI 2023)

Frangi, A., de Bruijne, Marleen, Wassermann, D. & Navab, N., 2023, Information Processing in Medical Imaging: 28th International Conference, IPMI 2023, San Carlos de Bariloche, Argentina, June 18–23, 2023, Proceedings. Springer, p. v-vi (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 13939 LNCS).

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Why is the winner the best?

Eisenmann, M., Reinke, A., Weru, V., Tizabi, M. D., Isensee, F., Adler, T. J., Ali, S., Andrearczyk, V., Aubreville, M., Baid, U., Bakas, S., Balu, N., Bano, S., Bernal, J., Bodenstedt, S., Casella, A., Cheplygina, V., Daum, M., Bruijne, M. D., Depeursinge, A. & 105 others, Dorent, R., Egger, J., Ellis, D. G., Engelhardt, S., Ganz, Melanie, Ghatwary, N., Girard, G., Godau, P., Gupta, A., Hansen, L., Harada, K., Heinrich, M., Heller, N., Hering, A., Huaulmé, A., Jannin, P., Kavur, A. E., Kodym, O., Kozubek, M., Li, J., Li, H., Ma, J., Martín-Isla, C., Menze, B., Noble, A., Oreiller, V., Padoy, N., Pati, S., Payette, K., Rädsch, T., Rafael-Patiño, J., Bawa, V. S., Speidel, S., Sudre, C. H., Wijnen, K. V., Wagner, M., Wei, D., Yamlahi, A., Yap, M. H., Yuan, C., Zenk, M., Zia, A., Zimmerer, D., Aydogan, D. B., Bhattarai, B., Bloch, L., Brüngel, R., Cho, J., Choi, C., Dou, Q., Ezhov, I., Friedrich, C. M., Fuller, C., Gaire, R. R., Galdran, A., Faura, Á. G., Grammatikopoulou, M., Hong, S., Jahanifar, M., Jang, I., Kadkhodamohammadi, A., Kang, I., Kofler, F., Kondo, S., Kuijf, H., Li, M., Luu, M. H., Martinčič, T., Morais, P., Naser, M. A., Oliveira, B., Owen, D., Pang, S., Park, J., Park, S., Płotka, S., Puybareau, E., Rajpoot, N., Ryu, K., Saeed, N., Shephard, A., Shi, P., Štepec, D., Subedi, R., Tochon, G., Torres, H. R., Urien, H., Vilaça, J. L., Wahid, K. A., Wang, H., Wang, J., Wang, L., Wang, X., Wiestler, B., Wodzinski, M., Xia, F., Xie, J., Xiong, Z., Yang, S., Yang, Y., Zhao, Z., Maier-Hein, K., Jäger, P. F., Kopp-Schneider, A. & Maier-Hein, L., 2023, Proceedings - 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2023. IEEE Computer Society Press, p. 19955-19966

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Learning from Imperfect Data: Weak Labels, Shifting Domains, and Small Datasets in Medical Imaging

de Bruijne, Marleen, 2021, Bildverarbeitung für die Medizin 2021: Proceedings, German Workshop on Medical Image Computing, Regensburg, March 7-9, 2021. Springer, p. 1 1 p.

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Preface

Ernst, F., Heinrich, M., Lellmann, J., Schlaefer, A., Dou, Q. & de Bruijne, Marleen, 2021, e Proceedings of the Fourth International Conference on Medical Imaging with Deep Learning – MIDL 2021. PMLR, p. 1-4 (Proceedings of Machine Learning Research, Vol. 143).

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Preface (vols 1-8)

de Bruijne, Marleen, Cattin, P. C., Cotin, S., Padoy, N., Speidel, S., Zheng, Y. & Essert, C., 2021, Medical Image Computing and Computer Assisted Intervention – MICCAI 2021: 24th International Conference, Strasbourg, France, September 27 – October 1, 2021, Proceedings, Part VII. Springer, Vol. 12905 LNCS. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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Uncertainty-Based Segmentation of Myocardial Infarction Areas on Cardiac MR Images

Camarasa, R., Faure, A., Crozier, T., Bos, D. & de Bruijne, Marleen, 2021, Statistical Atlases and Computational Models of the Heart. MandMs and EMIDEC Challenges - 11th International Workshop, STACOM 2020, Held in Conjunction with MICCAI 2020, Revised Selected Papers. Puyol Anton, E., Pop, M., Sermesant, M., Campello, V., Lalande, A., Lekadir, K., Suinesiaputra, A., Camara, O. & Young, A. (eds.). Springer, p. 385-391 7 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 12592 LNCS).

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Spectral Data Augmentation Techniques to Quantify Lung Pathology from CT-Images

Kayal, S., Dubost, F., Tiddens, H. A. W. M. & de Bruijne, Marleen, Apr 2020, ISBI 2020 - 2020 IEEE International Symposium on Biomedical Imaging. IEEE, p. 586-590 9098581

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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).

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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).

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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).

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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).

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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).

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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).

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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).

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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).

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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).

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Multi-task Attention-Based Semi-supervised Learning for Medical Image Segmentation

Chen, S., Bortsova, G., Juárez, A. G. U., van Tulder, G. & 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. 457-465 9 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 11766 LNCS).

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Semi-supervised Medical Image Segmentation via Learning Consistency Under Transformations

Bortsova, G., Dubost, F., Hogeweg, L., Katramados, I. & 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. 810-818 9 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 11769 LNCS).

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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).

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Deep Multi-instance Volumetric Image Classification with Extreme Value Distributions

Tennakoon, R., Gostar, A. K., Hoseinnezhad, R., de Bruijne, Marleen & Bab-Hadiashar, A., 2019, Computer Vision - ACCV 2018: 14th Asian Conference on Computer Vision, Perth, Australia, December 2–6, 2018, Revised Selected Papers. Li, H., Jawahar, C. V., Mori, G. & Schindler, K. (eds.). Springer, p. 590-604 15 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 11363 LNCS).

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Event-Based Modeling with High-Dimensional Imaging Biomarkers for Estimating Spatial Progression of Dementia

for the Alzheimer’s Disease Neuroimaging Initiative, F. A. D. N. I., 2019, Information Processing in Medical Imaging - 26th International Conference, IPMI 2019, Proceedings: 26th International Conference, IPMI 2019, Hong Kong, China, June 2–7, 2019,Proceedings. Bao, S., Chung, A. C. S., Gee, J. C. & Yushkevich, P. A. (eds.). Springer, p. 169-180 12 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 11492 LNCS).

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Detecting emphysema with multiple instance learning

Orting, S. N., Petersen, Jens, Thomsen, L. H., Wille, M. M. W. & de Bruijne, Marleen, 23 May 2018, 2018 IEEE 15th International Symposium on Biomedical Imaging, ISBI 2018. IEEE, p. 510-513

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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).

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Automatic airway segmentation in chest CT using convolutional neural networks

Juarez, A. G. U., Tiddens, H. A. W. M. & de Bruijne, Marleen, 2018, Image Analysis for Moving Organ, Breast, and Thoracic Images: Third International Workshop, RAMBO 2018, Fourth International Workshop, BIA 2018, and First International Workshop, TIA 2018, Held in Conjunction with MICCAI 2018, Proceedings. Springer, p. 238-250 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 11040 LNCS).

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Deep Learning from Label Proportions for Emphysema Quantification

Bortsova, G., Dubost, F., Ørting, S., Katramados, I., Hogeweg, L., Thomsen, L., Wille, M. & de Bruijne, Marleen, 2018, Medical Image Computing and Computer Assisted Intervention – MICCAI 2018: 21st International Conference, 2018, Proceedings Part II. Frangi, A. F., Schnabel, J. A., Davatzikos, C., Alberola-López, C. & Fichtinger, G. (eds.). Springer, p. 768-776 (Lecture notes in computer science, Vol. 11071).

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Feature Learning Based on Visual Similarity Triplets in Medical Image Analysis: A Case Study of Emphysema in Chest CT Scans

Nyboe Ørting, S., Petersen, Jens, Cheplygina, V., Thomsen, L. H., Wille, M. M. W. & de Bruijne, Marleen, 2018, Intravascular Imaging and Computer Assisted Stenting and Large-Scale Annotation of Biomedical Data and Expert Label Synthesis: 7th Joint International Workshop, CVII-STENT 2018 and Third International Workshop, LABELS 2018 Held in Conjunction with MICCAI 2018 Granada, Spain, September 16, 2018 Proceedings. Stoyanov, D., Taylor, Z., Balocco, S. & Sznitman, R. (eds.). Springer, p. 140-149 Chapter 16. (Lecture Notes in Computer Science, Vol. 11043).

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Mean Field Network Based Graph Refinement with Application to Airway Tree Extraction

Selvan, Raghav, Welling, M., Pedersen, J. J. H., Petersen, Jens & de Bruijne, Marleen, 2018, Medical Image Computingand Computer AssistedIntervention – MICCAI 2018: 21st International Conference, Granada, Spain, September 16–20, 2018, Proceedings, Part II. Frangi, A. F., Schnabel, J. A., Davatzikos, C., Alberola-López, C. & Fichtinger, G. (eds.). Springer, p. 750-758 (Lecture notes in computer science, Vol. 11071).

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Quantification of Lung Abnormalities in Cystic Fibrosis using Deep Networks

Marques, F., Dubost, F., Corput, M. K. D., Tiddens, H. A. W. & de Bruijne, Marleen, 2018, Medical Imaging 2018: Image Processing. SPIE - International Society for Optical Engineering, 7 p. 105741G. (Proceedings of SPIE International Symposium on Medical Imaging, Vol. 10574).

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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).

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Do you trust your multiple instance learning classifier?

Cheplygina, V., Sørensen, L., Tax, D. M. J., de Bruijne, Marleen & Loog, M., 2017, Benelearn 2017: Proceedings of the Twenty-Sixth Benelux Conference on Machine Learning. Duivesteijn, W., Pechenizkiy, M., Fletcher, G., Menkovski, V., Postma, E., Vanschoren, J. & van der Putten, P. (eds.). p. 72-73 2 p.

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Extraction of Airways with Probabilistic State-Space Models and Bayesian Smoothing

Selvan, Raghav, Petersen, Jens, Pedersen, J. J. H. & de Bruijne, Marleen, 2017, Graphs in Biomedical Image Analysis, Computational Anatomy and Imaging Genetics: First International Workshop, GRAIL 2017, 6th International Workshop, MFCA 2017, and Third International Workshop, MICGen 2017, Held in Conjunction with MICCAI 2017, Québec City, QC, Canada, September 10–14, 2017, Proceedings. Cardoso, M. J., Arbel, T., Ferrante, E., Pennec, X., Dalca, A. V., Parisot, S., Joshi, S., Batmanghelich, N. K., Sotiras, A., Nielsen, M., Sabuncu, M. R., Fletcher, T., Shen, L., Durrleman, S. & Sommer, S. (eds.). Springer, p. 53-63 (Lecture notes in computer science, Vol. 10551).

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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).

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Representation learning for cross-modality classification

Tulder, G. V. & de Bruijne, Marleen, 2017, Medical Computer Vision and Bayesian and Graphical Models for Biomedical Imaging: MICCAI 2016 International Workshops, MCV and BAMBI, Athens, Greece, October 21, 2016, Revised Selected Papers. Müller, H., Kelm, B. M., Arbel, T., Cai, W., Cardoso, M. J., Langs, G., Menze, B., Metaxas, D., Montillo, A., Wells, W. M., Zhang, S., Chung, A. C. S., Jenkinson, M. & Ribbens, A. (eds.). Springer, p. 126-136 11 p. (Lecture notes in computer science, Vol. 10081).

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Segmentation of intracranial arterial calcification with deeply supervised residual dropout networks

Bortsova, G., van Tulder, G., Dubost, F., Peng, T., Navab, N., van der Lugt, A., Bos, D. & 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. & Duchesne, S. (eds.). Springer, p. 356-364 9 p. (Lecture notes in computer science, Vol. 10435).

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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.

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Early experiences with crowdsourcing airway annotations in chest CT

Cheplygina, V., Perez-Rovira, A., Kuo, W., Tiddens, H. A. W. M. & de Bruijne, Marleen, 2016, Deep Learning and Data Labeling for Medical Applications: First International Workshop, LABELS 2016, and Second International Workshop, DLMIA 2016, Held in Conjunction with MICCAI 2016, Athens, Greece, October 21, 2016, Proceedings. Carneiro, G., Mateus, D., Peter, L., Bradley, A., Tavares, J. M. R. S., Belagiannis, V., Papa, J. P., Nascimento, J. C., Loog, M., Lu, Z., Cardoso, J. S. & Cornebise, J. (eds.). Springer, p. 209-218 10 p. (Lecture notes in computer science, Vol. 10008).

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Extraction of airway trees using multiple hypothesis tracking and template matching

Selvan, Raghav, Petersen, Jens, Pedersen, J. J. H. & de Bruijne, Marleen, 2016, The Sixth International Workshop on Pulmonary Image Analysis: Athens, Greece - October 21, 2016. Beichel, R. R., Farahani, K., Jacobs, C., Kabus, S., Kiraly, A. P., Kuhnigk, J-M., McClelland, J. R., Mori, K., Petersen, J. & Rit, S. (eds.). Create Space Independent Publishing Platform, p. 43-54 12 p.

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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.

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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).

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Label stability in multiple instance learning

Cheplygina, V., Sørensen, L., Tax, D. M. J., de Bruijne, Marleen & Loog, M., 2015, Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015: 18th international conference, Munich, Germany, October 5-9, 2015, Proceedings, Part I. Navab, N., Hornegger, J., Wells, W. M. & Frangi, A. F. (eds.). Springer, p. 539-546 8 p. (Lecture notes in computer science).

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Quantification and visualization of variation in anatomical trees

Amenta, N., Datar, M., Dirksen, A., de Bruijne, Marleen, Feragen, A., Ge, X., Pedersen, J., Howard, M., Owen, M., Petersen, Jens, Shi, J. & Xu, Q., 2015, Research in shape modeling. Leonard, K. & Tari, S. (eds.). Springer, p. 57-79 23 p. (Association for Women in Mathematics Series, Vol. 1).

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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).

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Classification of COPD with multiple instance learning

Cheplygina, V., Sørensen, L. E. B. L., Tax, D., Pedersen, J. J. H., Loog, M. & de Bruijne, Marleen, 2014, 22nd International Conference on Pattern Recognition (ICPR) 2014. IEEE, p. 1508-1513 6 p. (International Conference on Pattern Recognition).

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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).

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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).

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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

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).

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Carotid artery lumen segmentation in 3D free-hand ultrasound images using surface graph cuts

Lorza, A. M. A., Carvalho, D. D. B., Petersen, Jens, Dijk, A. C. V., Lugt, A. V. D., Niessen, W. J., Klein, S. & de Bruijne, Marleen, 2013, Medical Image Computing and Computer-Assisted Intervention – MICCAI 2013: 16th International Conference, Nagoya, Japan, September 22-26, 2013, Proceedings, Part II. Mori, K., Sakuma, I., Sato, Y., Barillot, C. & Navab, N. (eds.). Springer, p. 542-549 8 p. (Lecture notes in computer science, Vol. 8150).

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Carotid artery wall segmentation by coupled surface graph cuts

Arias, A., Petersen, Jens, van Engelen, A., Tang, H., Selwaness, M., Witteman, J. C. M., van der Lugt, A., Niessen, W. & de Bruijne, Marleen, 2013, Medical Computer Vision. Recognition techniques and applications in medical imaging: Second International MICCAI Workshop, MCV 2012, Nice, France, Revised Selected Papers. Menze, B. H., Langs, G., Lu, L., Montillo, A., Tu, Z. & Criminisi, A. (eds.). Springer, p. 38-47 10 p. (Lecture notes in computer science, Vol. 7766).

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Efficient nonrigid registration using ranked order statistics

Tennakoon, R. B., Bab-Hadiashar, A., de Bruijne, Marleen & Cao, Z., 2013, 2013 IEEE 10th International Symposium on Biomedical Imaging (ISBI). IEEE, p. 496-499 4 p. (International Symposium on Biomedical Imaging. Proceedings).

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Geometric tree kernels: classification of COPD from airway tree geometry

Feragen, A., Petersen, Jens, Grimm, D., Dirksen, A., Pedersen, J. J. H., Borgwardt, K. & de Bruijne, Marleen, 2013, Information Processing in Medical Imaging: 23rd International Conference, IPMI 2013, Asilomar, CA, USA, June 28–July 3, 2013. Proceedings. Gee, J. C., Joshi, S., Pohl, K. M., Wells, W. M. & Zöllei, L. (eds.). Springer, p. 171-183 13 p. (Lecture notes in computer science, Vol. 7917).

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Iterated stacked classifiers for lung segmentation in computed tomography

Ciompi, F., Gatta, C. & de Bruijne, Marleen, 2013, The Fifth International Workshop on Pulmonary Image Analysis: Nagoya, Japan - September 26, 2013. Beichel, R. R., de Bruijne, M., Kabus, S., Kiraly, A. P., Kitasaka, T., Kuhnigk, J-M., McClelland, J. R., van Rikxoort, E. & Rit, S. (eds.). CreateSpace Independent Publishing Platform , p. 63-74 12 p.

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Local appearance features for robust MRI brain structure segmentation across scanning protocols

Achterberg, H. C., Poot, D. H. J., van der Lijn, F., Vernooij, M. W., Ikram, M. A., Niessen, W. J. & de Bruijne, Marleen, 2013, Medical Imaging 2013: image processing . Ourselin, S. & Haynor, D. R. (eds.). SPIE - International Society for Optical Engineering, 7 p. 866905. (Progress in Biomedical Optics and Imaging; No. 36, Vol. 14).

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Quantitative airway analysis in longitudinal studies using groupwise registration and 4D optimal surfaces

Petersen, Jens, Modat, M., Cardoso, M. J., Dirksen, A., Ourselin, S. & de Bruijne, Marleen, 2013, Medical Image Computing and Computer-Assisted Intervention – MICCAI 2013: 16th International Conference, Nagoya, Japan, September 22-26, 2013, Proceedings, Part II. Mori, K., Sakuma, I., Sato, Y., Barillot, C. & Navab, N. (eds.). Springer, Vol. 2. p. 287-294 8 p. (Lecture notes in computer science, Vol. 8150).

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Scalable kernels for graphs with continuous attributes

Feragen, A., Kasenburg, N., Petersen, Jens, de Bruijne, Marleen & Borgwardt, K., 2013, 27th Annual Conference on Neural Information Processing Systems 2013: NIPS 2013. Burges, C. J. C., Bottou, L., Welling, M., Ghahramani, Z. & Weinberger, K. Q. (eds.). Curran Associates, Inc., p. 216-224 9 p. (Advances in Neural Information Processing Systems, Vol. 26).

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Tree-space statistics and approximations for large-scale analysis of anatomical trees

Feragen, A., Owen, M., Petersen, Jens, Wille, M. M. W., Thomsen, L. H., Dirksen, A. & de Bruijne, Marleen, 2013, Information Processing in Medical Imaging: 23rd International Conference, IPMI 2013, Asilomar, CA, USA, June 28–July 3, 2013. Proceedings. Gee, J. C., Joshi, S., Pohl, K. M., Wells, W. M. & Zöllei, L. (eds.). Springer, p. 74-85 12 p. (Lecture notes in computer science, Vol. 7917).

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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.

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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.

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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).

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Fluoroscopic assessment of femoral kinematics using a statistical shape model

Baka, N., de Bruijne, Marleen, van Walsum, T., Kaptein, B., Giphart, E., Schaap, M., Niessen, W. & Lelieveldt, B., 2012, EORS 2012 Amsterdam: European Orthopaedic Research Society 20th annual meeting. EORS , p. 147148 2 p. 5B.2

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