Erik Bjørnager Dam

Erik Bjørnager Dam

Professor

Medlem af:


    1. 2024
    2. Udgivet

      Advancing Kidney, Kidney Tumor, Cyst Segmentation: A Multi-Planner U-Net Approach for the KiTS23 Challenge

      Pandey, Sumit, Toshali, Perslev, Mathias & Dam, Erik Bjørnager, 2024, Kidney and Kidney Tumor Segmentation - MICCAI 2023 Challenge, KiTS 2023, Held in Conjunction with MICCAI 2023, Proceedings. Heller, N., Wood, A., Weight, C., Isensee, F., Rädsch, T., Teipaul, R. & Papanikolopoulos, N. (red.). Springer, s. 143-148 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Bind 14540 LNCS).

      Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

    3. Udgivet

      Operating Critical Machine Learning Models in Resource Constrained Regimes

      Selvan, Raghav, Schön, Julian Elisha & Dam, Erik Bjørnager, 2024, Medical Image Computing and Computer Assisted Intervention – MICCAI 2023 Workshops: MTSAIL 2023, LEAF 2023, AI4Treat 2023, MMMI 2023, REMIA 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8–12, 2023, Proceedings. Springer, s. 325-335 Chapter 29. (Lecture Notes in Computer Science, Bind 14394).

      Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

    4. 2023
    5. 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/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

    6. 2022
    7. 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/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

    8. 2021
    9. Udgivet

      Segmenting Two-Dimensional Structures with Strided Tensor Networks

      Selvan, Raghav, Dam, Erik Bjørnager & Petersen, Jens, 2021, Information Processing in Medical Imaging - 27th International Conference, IPMI 2021, Proceedings. Feragen, A., Sommer, S., Schnabel, J. & Nielsen, M. (red.). Springer, s. 401-414 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Bind 12729 LNCS).

      Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

    10. 2020
    11. Udgivet

      Tensor Networks for Medical Image Classification

      Selvan, Raghav & Dam, Erik Bjørnager, 21 apr. 2020, International Conference on Medical Imaging with Deep Learning, MIDL 2020, 6-8 July 2020, Montréal, QC, Canada. PMLR, s. 721-732 (Proceedings of Machine Learning Research, Bind 121).

      Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

    12. Udgivet

      Wheel rutting: preliminary investigations of soil redox potential and automated monitoring of their presence using machine learning and highresolution LiDAR data

      Callesen, Ingeborg, Brockmann, Bo, Fischer, Lene, Magnussen, A. & Dam, Erik Bjørnager, 2020, Forest Operations for the Future - Conference Proceedings. University of Copenhagen, s. 58-62 5 s.

      Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskning

    13. 2019
    14. Udgivet

      One Network to Segment Them All: A General, Lightweight System for Accurate 3D Medical Image Segmentation

      Perslev, Mathias, Dam, Erik Bjørnager, Pai, A. & Igel, Christian, 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. (red.). Springer VS, s. 30-38 9 s. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Bind 11765 LNCS).

      Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

    15. 2017
    16. 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/rapportBidrag til bog/antologiForskningfagfællebedømt

    17. 2013
    18. 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/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

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