Marleen de Bruijne

Search results

• 2025

  FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare

  Lekadir, K., Frangi, A. F., Porras, A. R., Glocker, B., Cintas, C., Langlotz, C. P., Weicken, E., Asselbergs, F. W., Prior, F., Collins, G. S., Kaissis, G., Tsakou, G., Buvat, I., Kalpathy-Cramer, J., Mongan, J., Schnabel, J. A., Kushibar, K., Riklund, K., Marias, K. & Amugongo, L. M. & 30 others, Fromont, L. A., Maier-Hein, L., Cerdá-Alberich, L., Martí-Bonmatí, L., Cardoso, M. J., Bobowicz, M., Shabani, M., Tsiknakis, M., Zuluaga, M. A., Fritzsche, M. C., Camacho, M., Linguraru, M. G., Wenzel, M., De Bruijne, M., Tolsgaard, M. G., Goisauf, M., Cano Abadía, M., Papanikolaou, N., Lazrak, N., Pujol, O., Osuala, R., Napel, S., Colantonio, S., Joshi, S., Klein, S., Aussó, S., Rogers, W. A., Salahuddin, Z., Starmans, M. P. A. & The FUTURE-AI Consortium, 2025, In: BMJ. 388, 22 p., e081554.

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  21 Citations (Scopus)

• Label refinement network from synthetic error augmentation for medical image segmentation

  Chen, S., Garcia-Uceda, A., Su, J., van Tulder, G., Wolff, L., van Walsum, T. & de Bruijne, M., 2025, In: Medical Image Analysis. 99, 11 p., 103355.

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• Leveraging Point Annotations in Segmentation Learning with Boundary Loss

  Breznik, E., Kervadec, H., Malmberg, F., Kullberg, J., Ahlström, H., de Bruijne, M. & Strand, R., 2025, Pattern Recognition - 27th International Conference, ICPR 2024, Proceedings. Antonacopoulos, A., Chaudhuri, S., Chellappa, R., Liu, C.-L., Bhattacharya, S. & Pal, U. (eds.). Springer, p. 194-210 17 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 15313 LNCS).

  Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

• Morphology of the dysplastic hip and the relationship with sex and acetabular version

  Mechlenburg, I., De Raedt, S., Achterberg, H. C., Stilling, M., Rømer, L., Søballe, K. & de Bruijne, M., 2025, (E-pub ahead of print) In: Clinical Anatomy.

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  1 Citation (Scopus)

• Normative values for lung, bronchial sizes, and bronchus-artery ratios in chest CT scans: from infancy into young adulthood

  Lv, Q., Chen, Y., Caudri, D., Andrinopoulou, E. R., Kuo, W., Charbonnier, J. P., Fleck, R. J., Soler, L. R., Paoletti, M., Vermeulen, F., Morana, G., Lee, E. Y., de Bruijne, M., Tiddens, H. A. W. M., Ciet, P., Stick, S. M., Odink, A. E., Mol, C. P., McCartin, M. & Lindblad, A. & 9 others, Gartner, S., Garcia-Peña, P., Fraioli, F., de Jong, P. A., de Boeck, K., Brody, A. S., Bertolo, S., Akesson, L. & for the Normal Chest CT Study Group, 2025, (E-pub ahead of print) In: European Radiology.

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• Reference formulas for chest CT-derived lobar volumes in the lung-healthy general population

  Bakker, J. T., Dudurych, I., Roodenburg, S. A., Vonk, J. M., Klooster, K., de Bruijne, M., van den Berge, M., Slebos, D. J. & Vliegenthart, R., 2025, In: European Radiology. 35, p. 2912–2921

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• 2024

  Automatic analysis of bronchus-artery dimensions to diagnose and monitor airways disease in cystic fibrosis

  Lv, Q., Gallardo-Estrella, L., Andrinopoulou, E.-R., Chen, Y., Charbonnier, J.-P., Sandvik, R. M., Caudri, D., Nielsen, K. G., de Bruijne, M., Ciet, P. & Tiddens, H., 2024, In: Thorax. p. 13-22

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  12 Citations (Scopus)

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• Burden of intracranial artery calcification in white patients with ischemic stroke

  Berghout, B. P., Camarasa, R. Y. R., Van Dam-Nolen, D. H. K., van der Lugt, A., de Bruijne, M., Koudstaal, P. J., Ikram, M. K. & Bos, D., 2024, In: European Stroke Journal. 9, 3, p. 743-750

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• 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, M., 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).

  Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

• Low-Dose CT-derived Bronchial Parameters in Individuals with Healthy Lungs

  Dudurych, I., Pelgrim, G.-J., Sidorenkov, G., Garcia-Uceda, A., Petersen, J., Slebos, D.-J., de Bock, G. H., van den Berge, M., de Bruijne, M. & Vliegenthart, R., 2024, In: Radiology. 311, 3, 9 p., e232677.

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  4 Citations (Scopus)

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• Where is VALDO? VAscular Lesions Detection and segmentatiOn challenge at MICCAI 2021

  ALFA study, 2024, In: Medical Image Analysis. 91, 23 p., 103029.

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  11 Citations (Scopus)

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• 2023

  Determinants of Perivascular Spaces in the General Population: A Pooled Cohort Analysis of Individual Participant Data

  Evans, T. E., Knol, M. J., Schwingenschuh, P., Wittfeld, K., Hilal, S., Ikram, M. A., Dubost, F., Van Wijnen, K. M. H., Katschnig, P., Yilmaz, P., De Bruijne, M., Habes, M., Chen, C., Langer, S., Völzke, H., Ikram, M. K., Grabe, H. J., Schmidt, R., Adams, H. H. H. & Vernooij, M. W., 2023, In: Neurology. 100, 2, p. E107-E122

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  33 Citations (Scopus)

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• Editorial for the MEDIA MICCAI special issue 2021

  de Bruijne, M., Cattin, P. C., Cotin, S., Padoy, N., Speidel, S., Zheng, Y. & Essert, C., Jan 2023, In: Medical Image Analysis. 83, 1 p., 102695.

  Research output: Contribution to journal › Editorial › Research

• Graph cut-based segmentation

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

  Research output: Chapter in Book/Report/Conference proceeding › Book chapter › Research › peer-review

• Nested star-shaped objects segmentation using diameter annotations

  Camarasa, R., Kervadec, H., Kooi, M. E., Hendrikse, J., Nederkoorn, P. J., Bos, D. & de Bruijne, M., 2023, In: Medical Image Analysis. 90, 11 p., 102934.

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  2 Citations (Scopus)

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• Preface: Information Processing in Medical Imaging (IPMI 2023)

  Frangi, A., de Bruijne, M., 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).

  Research output: Chapter in Book/Report/Conference proceeding › Preface/postscript › Research

• Reproducibility of a combined artificial intelligence and optimal-surface graph-cut method to automate bronchial parameter extraction

  Dudurych, I., Garcia-Uceda, A., Petersen, J., Du, Y., Vliegenthart, R. & de Bruijne, M., 2023, In: European Radiology. 33, p. 6718–6725

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  5 Citations (Scopus)

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• The effect of CFTR modulators on structural lung disease in cystic fibrosis

  Mok, L. C., Garcia-Uceda, A., Cooper, M. N., Kemner-Van De Corput, M., De Bruijne, M., Feyaerts, N., Rosenow, T., De Boeck, K., Stick, S. & Tiddens, H. A. W. M., 2023, In: Frontiers in Pharmacology. 14, 10 p., 1147348.

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  6 Citations (Scopus)

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• Unpaired, unsupervised domain adaptation assumes your domains are already similar

  van Tulder, G. & de Bruijne, M., 2023, In: Medical Image Analysis. 87, 17 p., 102825.

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  2 Citations (Scopus)

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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, M., 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.-H., 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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  14 Citations (Scopus)

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• 2022

  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, M., Feb 2022, In: Medical Image Analysis. 76, p. 1-12 102311.

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  32 Citations (Scopus)

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• Bronchial wall parameters on CT in healthy never-smoking, smoking, COPD, and asthma populations: a systematic review and meta-analysis

  Dudurych, I., Muiser, S., McVeigh, N., Kerstjens, H. A. M., van den Berge, M., de Bruijne, M. & Vliegenthart, R., 2022, In: European Radiology. 32, p. 5308–5318

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  10 Citations (Scopus)

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• Deep learning methods for automatic evaluation of delayed enhancement-MRI. The results of the EMIDEC challenge

  Lalande, A., Chen, Z., Pommier, T., Decourselle, T., Qayyum, A., Salomon, M., Ginhac, D., Skandarani, Y., Boucher, A., Brahim, K., de Bruijne, M., Camarasa, R., Correia, T. M., Feng, X., Girum, K. B., Hennemuth, A., Huellebrand, M., Hussain, R., Ivantsits, M. & Ma, J. & 13 others, Meyer, C., Sharma, R., Shi, J., Tsekos, N. V., Varela, M., Wang, X., Yang, S., Zhang, H., Zhang, Y., Zhou, Y., Zhuang, X., Couturier, R. & Meriaudeau, F., 2022, In: Medical Image Analysis. 79, p. 1-12 102428.

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  33 Citations (Scopus)

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• Diaphragmatic dysfunction in neuromuscular disease, an MRI study

  Harlaar, L., Ciet, P., van Tulder, G., Brusse, E., Timmermans, R. G. M., Janssen, W. G. M., de Bruijne, M., van der Ploeg, A. T., Tiddens, H. A. W. M., van Doorn, P. A. & van der Beek, N. A. M. E., 2022, In: Neuromuscular Disorders. 32, 1, p. 15-24

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  8 Citations (Scopus)

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• Differentiable Boundary Point Extraction for Weakly Supervised Star-shaped Object Segmentation

  Camarasa, R., Kervadec, H., Bos, D. & de Bruijne, M., 2022, In: Proceedings of Machine Learning Research. 172, p. 188-198

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  2 Citations (Scopus)

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• DS6, Deformation-Aware Semi-Supervised Learning: Application to Small Vessel Segmentation with Noisy Training Data

  Chatterjee, S., Prabhu, K., Pattadkal, M., Bortsova, G., Sarasaen, C., Dubost, F., Mattern, H., de Bruijne, M., Speck, O. & Nürnberger, A., 22 Sept 2022, In: Journal of Imaging. 8, 10, p. 1-22 259.

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  9 Citations (Scopus)

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• MRI changes in diaphragmatic motion and curvature in Pompe disease over time

  Harlaar, L., Ciet, P., van Tulder, G., van Kooten, H. A., van der Beek, N. A. M. E., Brusse, E., de Bruijne, M., Tiddens, H. A. W. M., van der Ploeg, A. T. & van Doorn, P. A., 2022, In: European Radiology. 32, p. 8681–8691

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  4 Citations (Scopus)

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• Sleep and perivascular spaces in the middle-aged and elderly population

  Lysen, T. S., Yilmaz, P., Dubost, F., Ikram, M. A., de Bruijne, M., Vernooij, M. W. & Luik, A. I., 2022, In: Journal of Sleep Research. 31, 2, p. 1-* e13485.

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  13 Citations (Scopus)

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• 2021

  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, M., 2021, In: Medical Image Analysis. 73, 14 p., 102141.

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  68 Citations (Scopus)

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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. & Bruijne, M. D., 22 Sept 2021, In: The Journal of Machine Learning for Biomedical Imaging. 2021, p. 1-39 013.

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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, M., 2021, In: Medical Physics. 48, 12, p. 7837-7849

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  5 Citations (Scopus)

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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, M., Sept 2021, In: Radiology: Artificial Intelligence. 3, 5, 10 p., e200226.

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  14 Citations (Scopus)

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• Automatic airway segmentation from computed tomography using robust and efficient 3-D convolutional neural networks

  Garcia-uceda, A., Selvan, R., Saghir, Z., Tiddens, H. A. W. M. & De Bruijne, M., 2021, In: Scientific Reports. 11, 1, 15 p., 16001.

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  39 Citations (Scopus)

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• Chest MRI to diagnose early diaphragmatic weakness in Pompe disease

  Harlaar, L., Ciet, P., van Tulder, G., Pittaro, A., van Kooten, H. A., van der Beek, N. A. M. E., Brusse, E., Wielopolski, P. A., de Bruijne, M., van der Ploeg, A. T., Tiddens, H. A. W. M. & van Doorn, P. A., 2021, In: Orphanet Journal of Rare Diseases. 16, 1, p. 1-12 21.

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  9 Citations (Scopus)

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• Creating a training set for artificial intelligence from initial segmentations of airways

  Dudurych, I., Garcia-Uceda, A., Saghir, Z., Tiddens, H. A. W. M., Vliegenthart, R. & de Bruijne, M., 2021, In: European radiology experimental. 5, 1, 7 p., 54.

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  6 Citations (Scopus)

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• Crowdsourcing airway annotations in chest computed tomography images

  Cheplygina, V., Perez-Rovira, A., Kuo, W., Tiddens, H. A. W. M. & de Bruijne, M., 2021, In: PLoS ONE. 16, e0249580.

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• Developing and validating COVID-19 adverse outcome risk prediction models from a bi-national European cohort of 5594 patients

  Jimenez-Solem, E., Petersen, T. S., Hansen, C., Hansen, C., Lioma, C., Igel, C., Boomsma, W., Krause, O., Lorenzen, S., Selvan, R., Petersen, J., Nyeland, M. E., Ankarfeldt, M. Z., Virenfeldt, G. M., Winther-Jensen, M., Linneberg, A., Ghazi, M. M., Detlefsen, N., Lauritzen, A. D. & Smith, A. G. & 15 others, de Bruijne, M., Ibragimov, B., Petersen, J., Lillholm, M., Middleton, J., Mogensen, S. H., Thorsen-Meyer, H.-C., Perner, A., Helleberg, M., Kaas-Hansen, B. S., Bonde, M., Bonde, A., Pai, A., Nielsen, M. & Sillesen, M., 2021, In: Scientific Reports. 11, 1, 12 p., 3246.

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• Intracranial arteriosclerosis is related to cerebral small vessel disease: a prospective cohort study

  Vinke, E. J., Yilmaz, P., van der Toorn, J. E., Fakhry, R., Frenzen, K., Dubost, F., Licher, S., de Bruijne, M., Kavousi, M., Ikram, M. A., Vernooij, M. W. & Bos, D., 2021, In: Neurobiology of Aging. 105, p. 16-24

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

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

  Research output: Chapter in Book/Report/Conference proceeding › Conference abstract in proceedings › Research

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• Preface

  Ernst, F., Heinrich, M., Lellmann, J., Schlaefer, A., Dou, Q. & de Bruijne, M., 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, M., 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)).

  Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research

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

  Camarasa, R., Faure, A., Crozier, T., Bos, D. & de Bruijne, M., 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).

  Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
  3 Citations (Scopus)
• 2020

  Airway tapering: An objective image biomarker for bronchiectasis

  Kuo, W., Perez-Rovira, A., Tiddens, H. & de Bruijne, M., 2020, In: European Radiology. 30, 5, p. 2703-2711

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  23 Citations (Scopus)

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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, M., 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
  9 Citations (Scopus)

• Chronic Obstructive Pulmonary Disease Quantification Using CT Texture Analysis and Densitometry: Results From the Danish Lung Cancer Screening Trial

  Sørensen, L., Nielsen, M., Petersen, J., Pedersen, J. H., Dirksen, A. & de Bruijne, M., 2020, In: American Journal of Roentgenology. 214, 6, p. 1269-1279

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  24 Citations (Scopus)

• Classification of Volumetric Images Using Multi-Instance Learning and Extreme Value Theorem

  Tennakoon, R., Bortsova, G., Orting, S., Gostar, A. K., Wille, M. M. W., Saghir, Z., Hoseinnezhad, R., de Bruijne, M. & Bab-Hadiashar, A., 2020, In: IEEE Transactions on Medical Imaging. 39, 4, p. 854-865

  Research output: Contribution to journal › Journal article › Research › peer-review

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  17 Citations (Scopus)

  32 Downloads (Pure)

• Graph Refinement based Airway Extraction using Mean-Field Networks and Graph Neural Networks

  Selvan, R., Kipf, T., Welling, M., Juarez, A.G.-U., Pedersen, J. H., Petersen, J. & Bruijne, M. D., 2020, In: Medical Image Analysis. 64, 12 p., 101751.

  Research output: Contribution to journal › Journal article › Research › peer-review

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  22 Citations (Scopus)

• Growth of the thoracic aorta in the smoking population: The Danish Lung Cancer Screening Trial

  Bons, L. R., Sedghi Gamechi, Z., Thijssen, C. G. E., Kofoed, K. F., Pedersen, J. H., Saghir, Z., Takkenberg, J. J. M., Kardys, I., Budde, R. P. J., de Bruijne, M. & Roos-Hesselink, J. W., 2020, In: International Journal of Cardiology. 299, p. 276-281

  Research output: Contribution to journal › Journal article › Research › peer-review
  9 Citations (Scopus)

• Learning to quantify emphysema extent: What labels do we need?

  Orting, S. N., Petersen, J., Thomsen, L. H., Winkler Wille, M. M. & Bruijne, M. D., 2020, In: IEEE Journal of Biomedical and Health Informatics. 24, 4, p. 1149 -1159

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• Longitudinal assessment of carotid plaque texture in three-dimensional ultrasound images based on semi-supervised graph-based dimensionality reduction and feature selection

  Lin, M., Cui, H., Chen, W., van Engelen, A., de Bruijne, M., Azarpazhooh, M. R., Sohrevardi, S. M., Spence, J. D. & Chiu, B., Jan 2020, In: Computers in Biology and Medicine. 116, 11 p., 103586.

  Research output: Contribution to journal › Journal article › Research › peer-review
  13 Citations (Scopus)