Erik Bjørnager Dam

Erik Bjørnager Dam

Professor

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    ORCID: 0000-0002-8888-2524

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    1. Published

      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, In: BMC Medical Imaging. 14, 1, 12 p., 21.

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

    2. Published

      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 p.

      Research output: Working paper › Preprint › Research

    3. Published

      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, p. 506–516 (Lecture Notes in Computer Science, Vol. 13435).

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

    4. Published

      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, In: Magnetic Resonance in Medicine. 80, 3, p. 1219-1232

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

    5. Published

      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

      Research output: Other contribution › Research

    6. Published

      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. (eds.). Academic Press, p. 223–242 20 p.

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

    7. Published

      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, p. 2584-2590

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

    8. Published

      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, In: Skeletal Radiology. 51, p. 1959–1966

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

    9. Published

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

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

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

    10. Published

      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. (eds.). Springer, p. 246-253 8 p. (Lecture notes in computer science, Vol. 8150).

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

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