Erik Bjørnager Dam

Erik Bjørnager Dam

Professor

Medlem af:


    1. Udgivet

      Segmentation of tumors in magnetic resonance brain images using an interactive multiscale watershed algorithm

      Letteboer, M. M. J., Olsen, O. F., Dam, Erik Bjørnager, Willems, P. W. A., Viergever, M. A. & Niessen, W. J., okt. 2004, I: Academic Radiology. 11, 10, s. 1125-38 14 s.

      Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

    2. Udgivet

      Diagnosis of osteoarthritis and prognosis of tibial cartilage loss by quantification of tibia trabecular bone from MRI

      Marques, J., Genant, H. K., Lillholm, Martin & Dam, Erik Bjørnager, 2013, I: Magnetic Resonance in Medicine. 70, 2, s. 568-575 8 s.

      Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

    3. Udgivet

      Deformation-based atrophy computation by surface propagation and its application to Alzheimer’s disease

      Pai, A. S. U., Sporring, Jon, Darkner, Sune, Dam, Erik Bjørnager, Lillholm, Martin, Jørgensen, D., Oh, J., Chen, G., Suhy, J., Sørensen, L. & Nielsen, Mads, 2016, I: SPIE Journal of Medical Imaging. 3, 1, 11 s., 014005.

      Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

    4. 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

    5. 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

    6. 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

    7. Udgivet
    8. 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

    9. Udgivet

      Knee Segmentation by Multiplanar Deep Learning Network – with data from OAI

      Perslev, Mathias, Pai, A. S. U., Igel, Christian & Dam, Erik Bjørnager, 2018. 1 s.

      Publikation: KonferencebidragKonferenceabstrakt til konferenceForskningfagfællebedømt

    10. 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 tidsskriftTidsskriftartikelForskningfagfællebedømt

    ID: 176815263