Rasmus Reinhold Paulsen

2025

Automated Estimation of Cardiac Stroke Volumes from Computed Tomography

Radutoiu, A. T., Youssef, Y. W. E., Diez, P. L., Sørensen, K. A., Lindeskog, M. B., Pham, M. H. C., Pedersen, J. J., Fuchs, A., Kofoed, K. F. & Paulsen, R. R., 2025, Proceedings of the 15th International Workshop on Statistical Atlases and Computational Models of the Heart. Springer, Vol. 15448. p. 22-32 (Lecture Notes in Computer Science).

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

2024

Deep reinforcement learning and convolutional autoencoders for anomaly detection of congenital inner ear malformations in clinical CT images

López Diez, P., Sundgaard, J. V., Margeta, J., Diab, K., Patou, F. & Paulsen, R. R., 2024, In: Computerized Medical Imaging and Graphics. 113, 10 p., 102343.

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Multi-modal deep learning for joint prediction of otitis media and diagnostic difficulty

Sundgaard, J. V., Hannemose, M. R., Laugesen, S., Bray, P., Harte, J., Kamide, Y., Tanaka, C., Paulsen, R. R. & Christensen, A. N., 2024, In: Laryngoscope Investigative Otolaryngology. 9, 1, 7 p., e1199.

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Peridevice leaks following left atrial appendage occlusion - analysis with morphology descriptive centerlines and explainable graph attention network

Lopez Diez, P., Margeta, J., Gómez-Herrero, J., Lulic, D., Willemen, Y., Kofoed, K. F., Backer, O. D. & Paulsen, R. R., 2024, Proceeding of 15^th STACOM workshop. Springer, 10 p. (Lecture Notes in Computer Science).

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Spatio-Temporal Neural Distance Fields for Conditional Generative Modeling of the Heart

Sørensen, K., Diez, P., Margeta, J., El Youssef, Y., Pham, M., Pedersen, J. J., Kuhl, T., de Backer, O., Kofoed, K., Camara, O. & Paulsen, R., 2024, Proceedings of the 27th International Conference on Medical Image Computing and Computer Assisted Intervention – MICCAI 2024. Springer, Vol. 15003. p. 422-432 (Lecture Notes in Computer Science).

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

2023

Multi-modal data generation with a deep metric variational autoencoder

Sundgaard, J. V., Hannemose, M. R., Laugesen, S., Harte, J., Kamide, Y., Tanaka, C., Paulsen, R. R. & Christensen, A. N., 2023, Proceedings of the Northern Lights Deep Learning Workshop 2023. Septentrio Academic Publishing, Vol. 4. 9 p.

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Neural Representation of Open Surfaces

Christiansen, T. V., Bærentzen, J. A., Paulsen, R. R. & Hannemose, M. R., 2023, In: Computer Graphics Forum. 42, 5, 13 p., e14916.

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Unsupervised classification of congenital inner ear malformations using DeepDiffusion for latent space representation

Lopez Diez, P., Margeta, J., Diab, K., Patou, F. & Paulsen, R. R., 2023, Proceedings of the 26^th International Conference on Medical Image Computing and Computer Assisted Intervention. Springer, Vol. 14224. p. 652–662

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2022

Accurate localization of inner ear regions of interests using deep reinforcement learning

Radutoiu, A.-T., Patou, F., Margeta, J., Paulsen, R. R. & Lopez Diez, P., 2022, Proceedings of the 13^th International Workshop on Machine Learning in Medical Imaging. Springer, p. 416-424

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A deep learning approach for detecting otitis media from wideband tympanometry measurements

Sundgaard, J. V., Bray, P., Laugesen, S., Harte, J., Kamide, Y., Tanaka, C., Christensen, A. N. & Paulsen, R. R., 2022, In: IEEE Journal of Biomedical and Health Informatics. 26, 7, p. 2974 - 2982 9735386.

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Comparison of prospective and retrospective motion correction in 3D-encoded neuroanatomical MRI

Slipsager, J. M., Glimberg, S. L., Højgaard, L., Paulsen, R. R., Wighton, P., Tisdall, M. D., Jaimes, C., Gagoski, B. A., Grant, P. E., van der Kouwe, A., Olesen, O. V. & Frost, R., 2022, In: Magnetic Resonance in Medicine. 87, 2, p. 629-645

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Deep Reinforcement Learning for Detection of Abnormal Anatomies

López Diez, P., Juhl , K. A., Sundgaard, J. V., Diab, H., Margeta, J., Patou, F. & Paulsen, R. R., 2022, In: Proceedings of the Northern Lights Deep Learning Workshop. 3, 8 p.

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Deep Reinforcement Learning for Detection of Inner Ear Abnormal Anatomy in Computed Tomography

Lopez Diez, P., Sørensen, K. A., Sundgaard, J. V., Diab, K., Margeta, J., Patou, F. & Paulsen, R. R., 2022, Proceedings of 25^th International Conference on Medical Image Computing and Computer Assisted Intervention. Vol. 13433. p. 697–706

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Inter-rater reliability of the diagnosis of otitis media based on otoscopic images and wideband tympanometry measurements

Sundgaard, J. V., Värendh, M., Nordström, F., Kamide, Y., Tanaka, C., Harte, J., Paulsen, R. R., Christensen, A. N., Bray, P. & Laugesen, S., 2022, In: International Journal of Pediatric Otorhinolaryngology. 153, 7 p., 111034.

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NUDF - Neural Unsigned Distance Fields for High Resolution 3D Medical Image Segmentation

Sorensen, K., Camara, O., Backer, O. D., Kofoed, K. F. & Paulsen, R. R., 2022, Proceedings of 19^th IEEE International Symposium on Biomedical Imaging. IEEE, 5 p.

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

SparseMeshCNN with Self-Attention for Segmentation of Large Meshes

Hansen, B., Lowes, M., Ørkild, T., Dahl, A., Dahl, V., De Backer, O., Camara, O., Paulsen, R., Ingwersen, C. & Sørensen, K., 2022, In: Proceedings of the Northern Lights Deep Learning Workshop. 3, 9 p.

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Was that so Hard? Estimating Human Classification Difficulty

Hannemose, M. R., Sundgaard, J. V., Ternov, N. K., Paulsen, R. R. & Christensen, A. N., 2022, Proceedings of Applications of Medical Artificial Intelligence . Springer Science and Business Media Deutschland GmbH, p. 88-97 (Lecture Notes in Computer Science, Vol. 13540).

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2021

Deep Learning Framework for Real-Time Estimation of in-silico Thrombotic Risk Indices in the Left Atrial Appendage

Morales Ferez, X., Mill, J., Juhl, K. A., Acebes, C., Iriart, X., Legghe, B., Cochet, H., De Backer, O., Paulsen, R. R. & Camara, O., 2021, In: Frontiers in Physiology. 12, 14 p., 694945.

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Deep metric learning for otitis media classification

Sundgaard, J. V., Harte, J., Bray, P., Laugesen, S., Kamide, Y., Tanaka, C., Paulsen, R. R. & Christensen, A. N., Jul 2021, In: Medical Image Analysis. 71, 9 p., 102034.

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Estimation of Apnea-Hypopnea Index using Deep Learning on 3D Craniofacial Scans

Hanif, U., Leary, E. B., Schneider, L. D., Paulsen, R. R., Morse, A. M., Blackman, A., Schweitzer, P. K., Kushida, C. A., Liu, S. Y., Jennum, P., Sorensen, H. B. D. & Mignot, E., 2021, In: IEEE Journal of Biomedical and Health Informatics. 25, 11, p. 4185-4194

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Exploring Movement Impairments in Patients With Parkinson's Disease Using the Microsoft Kinect Sensor: A Feasibility Study

Rudå, D., Einarsson, G., Andersen, A. S. S., Matthiassen, J. B., Correll, C. U., Winge, K., Clemmensen, L. K. H., Paulsen, R. R., Pagsberg, A. K. & Fink-Jensen, A., 2021, In: Frontiers in Neurology. 11, 9 p., 610614.

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Facial and Cochlear Nerves Characterization Using Deep Reinforcement Learning for Landmark Detection

López Diez, P., Sundgaard, J. V., Patou, F., Margeta, J. & Paulsen, R. R., 2021, Medical Image Computing and Computer Assisted Intervention. Springer, p. 519-528 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 12904).

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

Geometric Deep Learning for the Assessment of Thrombosis Risk in the Left Atrial Appendage

Morales, X., Mill, J., Simeon, G., Juhl, K. A., De Backer, O., Paulsen, R. R. & Camara, O., 2021, Functional Imaging and Modeling of the Heart. Ennis, D. B., Perotti, L. E. & Wang, V. Y. (eds.). Springer, p. 639-649 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 12738 LNCS).

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Implicit Neural Distance Representation for Unsupervised and Supervised Classification of Complex Anatomies

Juhl, K. A., Morales, X., de Backer, O., Camara, O. & Paulsen, R. R., 2021, Medical Image Computing and Computer Assisted Intervention. de Bruijne, M., Cattin, P. C., Cotin, S., Padoy, N., Speidel, S., Zheng, Y. & Essert, C. (eds.). Springer, p. 405-415 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 12902 LNCS).

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

2020

Deep Learning Surrogate of Computational Fluid Dynamics for Thrombus Formation Risk in the Left Atrial Appendage

Morales, X., Mill, J., Juhl, K. A., Olivares, A., Jimenez-Perez, G., Paulsen, R. R. & Camara, O., 2020, Statistical Atlases and Computational Models of the Heart. Multi-Sequence CMR Segmentation, CRT-EPiggy and LV Full Quantification Challenges.. Springer, p. 157-166 (Lecture Notes in Computer Science, Vol. 12009).

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Introduction to Medical Image Analysis

Paulsen, R. R. & Moeslund, T. B., 2020, Springer. 192 p. (Undergraduate Topics in Computer Science).

Research output: Book/Report › Book › Education › peer-review

In vivo imaging of the buccal mucosa shows loss of the endothelial glycocalyx and perivascular hemorrhages in pediatric Plasmodium falciparum malaria

Lyimo, E., Haslund, L. E., Ramsing, T., Wang, C. W., Efunshile, A. M., Manjurano, A., Makene, V., Lusingu, J., Theander, T. G., Kurtzhals, J. A. L., Paulsen, R. & Hempel, C., 2020, In: Infection and Immunity. 88, 3, 14 p., e00679-19.

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Measuring movements in adolescents with psychosis using the Microsoft Kinect sensor: a pilot study exploring a new tool for assessing aspects of antipsychotic‐induced parkinsonism

Rudå, D., Einarsson, G., Matthiassen, J. B., Correll, C. U., Jensen, K. G., Klauber, D. G., Richard, C. J., Andersen, A. S. S., Krøigaard, S., Møllegaard Jepsen, J. R., Fagerlund, B., Winge, K., Clemmesen, L. K. H., Pagsberg, A. K., Paulsen, R. R. & Fink‐Jensen, A., 2020, In: Child and Adolescent Mental Health. 25, 2, p. 79-94

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

Multi-planar whole heart segmentation of 3D CT images using 2D spatial propagation CNN

Sundgaard, J. V., Juhl, K. A., Kofoed, K. F. & Paulsen, R. R., 2020, Proceedings of SPIE. SPIE - International Society for Optical Engineering, Vol. 11313. 8 p. 113131Y. (Proceedings of SPIE - The International Society for Optical Engineering).

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Prediction of Patient Demographics using 3D Craniofacial Scans and Multi-view CNNs

Hanif, U. R., Paulsen, R. R., Leary, E. B., Mignot, E., Jennum, P. & Sørensen, H. B. D., 2020, Proceedings of the 42^nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society. IEEE, p. 1950-1953

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

Quantifying the Financial Savings of Motion Correction in Brain MRI: A Model-Based Estimate of the Costs Arising From Patient Head Motion and Potential Savings From Implementation of Motion Correction

Slipsager, J. M., Glimberg, S. L., Søgaard, J., Paulsen, R. R., Johannesen, H. H., Martens, P. C., Seth, A., Marner, L., Henriksen, O. M., Olesen, O. V. & Højgaard, L., 1 Jan 2020, In: Journal of Magnetic Resonance Imaging. 52, 3, p. 731-738

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2019

Guiding 3D U-nets with signed distance fields for creating 3D models from images

Juhl, K. A., Paulsen, R. R., Dahl, A. B., Dahl, V. A., De Backer, O., Kofoed, K. F. & Camara, O., 2019. 4 p.

Research output: Contribution to conference › Paper › Research › peer-review

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Markerless motion tracking and correction for PET, MRI, and simultaneous PET/MRI

Slipsager, J. M., Ellegaard, A. H., Glimberg, S. L., Paulsen, R. R., Tisdall, M. D., Wighton, P., van der Kouwe, A., Marner, L., Henriksen, O. M., Law, I. & Olesen, O. V., 2019, In: PLOS ONE. 14, 4, 17 p., e0215524.

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Multi-view Consensus CNN for 3D Facial Landmark Placement

Paulsen, R. R., Juhl, K. A., Haspang, T., Hansen, T., Ganz, M. & Einarsson, G., 2019, Proceedings of 14th Asian Conference on Computer Vision. Springer, p. 706-719 (Lecture Notes in Computer Science, Vol. 11361).

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Statistical Shape Clustering of Left Atrial Appendages

Slipsager, J. M., Juhl, K. A., Sigvardsen, P. E., Kofoed, K. F., Backer, O. D., Olivares, A. L., Camara, O. & Paulsen, R. R., 2019, Statistical Atlases and Computational Models of the Heart. Springer, p. 32–39 (Lecture Notes in Computer Science, Vol. 11395).

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

Wind Turbine Surface Damage Detection by Deep Learning Aided Drone Inspection Analysis

Shihavuddin, A., Chen, X., Fedorov, V., Christensen, A. N., Riis, N. A. B., Branner, K., Dahl, A. B. & Paulsen, R. R., 2019, In: Energies. 12, 4, 15 p., 676.

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2018

Can we train a single deep learning model to detect and segment nuclei images acquired with any microscope or staining modality?

Shihavuddin, A., Gawrilowicz, F., Jeppesen, N. & Paulsen, R. R., 2018.

Research output: Contribution to conference › Conference abstract for conference › Research › peer-review

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Computer Aided Identification of Motion Disturbances Related to Parkinson’s Disease

Einarsson, G., Clemmensen, L. K. H., Rudå, D., Fink-Jensen, A., Nielsen, J., Pagsberg, A., Winge, K. & Paulsen, R. R., 2018, International Workshop on PRedictive Intelligence In MEdicine. Springer, p. 1-8 8 p. (Lecture Notes in Computer Science, Vol. 11121).

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

Computerized feedback during colonoscopy training leads to improved performance: a randomized trial

Vilmann, A. S., Norsk, D., Svendsen, M. B. S., Reinhold, R., Svendsen, L. B., Park, Y. S. & Konge, L., 2018, In: Gastrointestinal Endoscopy. 88, 5, p. 869-876 8 p.

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FastSME: faster and smoother manifold extraction from 3D stack

Basu, S., Rexhepaj, E., Spassky, N., Genovesio, A., Paulsen, R. R. & Shihavuddin, A., 2018, Proceedings of the IEEE 2018 Conference on Computer Vision and Pattern Recognition. IEEE

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Patient-specific estimation of detailed cochlear shape from clinical CT images

Kjer, H. M., Fagertun, J., Wimmer, W., Gerber, N., Vera, S., Barazzetti, L., Mangado, N., Ceresa, M., Piella, G., Stark, T., Stauber, M., Reyes, M., Weber, S., Caversaccio, M., González Ballester, M. Á. & Paulsen, R. R., 2018, In: International Journal of Computer Assisted Radiology and Surgery. 13, 3, p. 389–396

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Perceptually motivated analysis of numerically simulated head-related transfer functions generated by various 3D surface scanning systems

Dinakaran, M., Brinkmann, F., Harder, S., Pelzer, R., Grosche, P., Paulsen, R. R. & Weinzierl, S., 2018. 1 p.

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2017

Creating Ultra Dense Point Correspondence Over the Entire Human Head

Paulsen, R. R., Marstal, K. K., Laugesen, S. & Harder, S., 2017, Lecture Notes in Computer Science: Image Analysis. Springer, Vol. 10270. p. 438-447 (Lecture Notes in Computer Science).

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Data Descriptor: A multiscale imaging and modelling dataset of the human inner ear

Gerber, N., Reyes, M., Barazzetti, L., Kjer, H. M., Vera, S., Stauber, M., Mistrik, P., Ceresa, M., Mangado, N., Wimmer, W., Stark, T., Paulsen, R. R., Weber, S., Caversaccio, M. & Gonzalez Ballester, M. A., 2017, In: Scientific Data. 4, 12 p., 170132.

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Foreign object detection in multispectral X-ray images of food items using sparse discriminant analysis

Einarsson, G., Jensen, J. N., Paulsen, R. R., Einarsdottir, H., Ersbøll, B. K., Dahl, A. B. & Christensen, L. B., 2017, SCIA 2017. Springer, Vol. 10269. p. 350-361 (Lecture Notes in Computer Science, Vol. 10269).

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

Medial structure generation for registration of anatomical structures

Vera, S., Gil, D., Kjer, H. M., Fagertun, J., Paulsen, R. R. & González Ballester, M. A., 2017, Skeletonization: Theory, Methods and Applications. Elsevier, p. 313-344

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

2016

A framework for geometry acquisition, 3-D printing, simulation, and measurement of head-related transfer functions with a focus on hearing-assistive devices

Harder, S., Paulsen, R. R., Larsen, M., Laugesen, S., Mihocic, M. & Majdak, P., 2016, In: Computer-Aided Design. 75-76, p. 39-46

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Automatic Model Generation Framework for Computational Simulation of Cochlear Implantation

Mangado Lopez, N., Ceresa, M., Duchateau, N., Kjer, H. M., Vera, S., Dejea Velardo, H., Mistrik, P., Paulsen, R. R., Fagertun, J., Noailly, J., Piella, G. & González Ballester, M. A., 2016, In: Annals of Biomedical Engineering. 44, 8, p. 2453-2463

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Cochlear implant electrode localization in post-operative CT using a spherical measure

Braithwaite, B. M., Kjer, H. M., Fagertun, J., González Ballester, M. A., Dhanasingh, A., Mistrik, P., Gerber, N. & Paulsen, R. R., 2016, Proceedings of the 13th IEEE International Symposium on Biomedical Imaging (ISBI 2016) . IEEE, p. 1329-1333

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Free-form image registration of human cochlear μCT data using skeleton similarity as anatomical prior

Kjer, H. M., Fagertun, J., Vera, S., Gil, D., González Ballester, M. A. & Paulsen, R. R., 2016, In: Pattern Recognition Letters. 76, June, p. 76-82

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Rasmus Reinhold Paulsen

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