Erik Bjørnager Dam

Erik Bjørnager Dam

Professor

Medlem af:

    ORCID: 0000-0002-8888-2524

    Udgivelsesår:
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    1. Udgivet

      Brain region's relative proximity as marker for Alzheimer's disease based on structural MRI

      Erleben, L. L., Sørensen, L. E., Pai, A. S. U., Dam, Erik Bjørnager, Nielsen, Mads & Initiative, A. D. N., 2014, I: BMC Medical Imaging. 14, 1, 12 s., 21.

      Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt

    2. Udgivet

      CHILI: Chemically-Informed Large-scale Inorganic Nanomaterials Dataset for Advancing Graph Machine Learning

      Friis-Jensen, Ulrik, Johansen, Frederik Lizak, Anker, Andy Sode, Dam, Erik Bjørnager, Jensen, K. M. Ø. & Selvan, Raghav, 2024, arxiv.org, 16 s.

      Publikation: Working paper › Preprint › Forskning

    3. Udgivet

      Carbon Footprint of Selecting and Training Deep Learning Models for Medical Image Analysis

      Selvan, Raghav, Bhagwat, N., Anthony, L. F. W., Kanding, B. & Dam, Erik Bjørnager, 2022, Medical Image Computing and Computer Assisted Intervention – MICCAI 2022: 25th International Conference Singapore, September 18–22, 2022 Proceedings, Part V. Springer, s. 506–516 (Lecture Notes in Computer Science, Bind 13435).

      Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt

    4. Udgivet

      Cartilage cavity: an MRI marker of cartilage lesions in knee OA with Data from CCBR, OAI, and PROOF

      Dam, Erik Bjørnager, Runhaar, J., Bierma-Zienstra, S. & Karsdal, M., 2018, I: Magnetic Resonance in Medicine. 80, 3, s. 1219-1232

      Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt

    5. Udgivet

      Characterising the Atomic Structure of Mono-Metallic Nanoparticles from X-Ray Scattering Data Using Conditional Generative Models

      Anker, Andy Sode, Kjær, E. T. S., Dam, Erik Bjørnager, Billinge, S. J. L., Jensen, K. M. Ø. & Selvan, Raghav, 17 jul. 2020

      Publikation: Andet › Andet bidrag › Forskning

    6. Udgivet

      Characterization of errors in deep learning-based brain MRI segmentation

      Pai, A. S. U., Teng, Y., Blair, J. P. M., Kallenberg, M. G. J., Dam, Erik Bjørnager, Sommer, Stefan Horst, Igel, Christian & Nielsen, Mads, 2017, Deep learning for medical image analysis. Zhou, S. K., Greenspan, H. & Shen, D. (red.). Academic Press, s. 223–242 20 s.

      Publikation: Bidrag til bog/antologi/rapport › Bidrag til bog/antologi › Forskning › fagfællebedømt

    7. Udgivet

      Comprehensive Multimodal Segmentation in Medical Imaging: Combining YOLOv8 with SAM and HQ-SAM Models

      Pandey, Sumit, Chen, K. F. & Dam, Erik Bjørnager, 2023, Proceedings - 2023 IEEE/CVF International Conference on Computer Vision Workshops, ICCVW 2023. IEEE, s. 2584-2590

      Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt

    8. Udgivet

      Conventional MRI-derived subchondral trabecular biomarkers and their association with knee cartilage volume loss as early as 1 year: a longitudinal analysis from Osteoarthritis Initiative

      Pishgar, F., Ashraf-Ganjouei, A., Dolatshahi, M., Guermazi, A., Zikria, B., Cao, X., Wan, M., Roemer, F. W., Dam, Erik Bjørnager & Demehri, S., 2022, I: Skeletal Radiology. 51, s. 1959–1966

      Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt

    9. Udgivet

      Cross‐Cohort Automatic Knee MRI Segmentation With Multi‐Planar U‐Nets

      Perslev, Mathias, Pai, A., Runhaar, J., Igel, Christian & Dam, Erik Bjørnager, 2022, I: Journal of Magnetic Resonance Imaging. 55, 2, s. 1650-1663

      Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt

    10. Udgivet

      Deep feature learning for knee cartilage segmentation using a triplanar convolutional neural network

      Prasoon, A., Petersen, P. K., Igel, Christian, Lauze, Francois Bernard, Dam, Erik Bjørnager & Nielsen, Mads, 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. (red.). Springer, s. 246-253 8 s. (Lecture notes in computer science, Bind 8150).

      Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt

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    ID: 176815263