Peidi Xu

Peidi Xu

Ph.d.-stipendiat, Ph.d.-studerende, Undervisningsassistent

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    1 - 4 ud af 4Pr. side: 10
    Sortering: Udgivelsesdato
    1. 2023
    2. Udgivet

      A hybrid approach to full-scale reconstruction of renal arterial network

      Xu, Peidi, von Holstein-Rathlou, Niels-Henrik, Søgaard, S. B., Gundlach, C., Sørensen, Charlotte Mehlin, Erleben, Kenny, Sosnovtseva, Olga & Darkner, Sune, 9 maj 2023, I: Scientific Reports. 13, 1, 15 s., 7569.

      Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt

    3. Udgivet

      Deep-learning-based segmentation of individual tooth and bone with periodontal ligament interface details for simulation purposes

      Xu, Peidi, Gholamalizadeh, T., nsv780, nsv780, Darkner, Sune & Erleben, Kenny, 2023, I: IEEE Access. 11, s. 102460-102470

      Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt

    4. Udgivet

      Extremely Weakly-Supervised Blood Vessel Segmentation with Physiologically Based Synthesis and Domain Adaptation

      Xu, Peidi, Lee, B., Sosnovtseva, Olga, Sørensen, Charlotte Mehlin, Erleben, Kenny & Darkner, Sune, 2023, Medical Image Learning with Limited and Noisy Data - 2nd International Workshop, MILLanD 2023, Held in Conjunction with MICCAI 2023, Proceedings. Xue, Z., Antani, S., Zamzmi, G., Yang, F., Rajaraman, S., Liang, Z., Huang, S. X. & Linguraru, M. G. (red.). Springer, s. 191-201 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Bind 14307 LNCS).

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

    5. 2022
    6. Udgivet

      Auto-segmentation of Hip Joints Using MultiPlanar UNet with Transfer Learning

      Xu, Peidi, nsv780, nsv780, Gholamalizadeh, T., Nielsen, Michael Bachmann, Erleben, Kenny & Darkner, Sune, 2022, Medical Image Learning with Limited and Noisy Data: First International Workshop, MILLanD 2022 Held in Conjunction with MICCAI 2022 Singapore, September 22, 2022 Proceedings. Zamzmi, G., Antani, S., Rajaraman, S., Xue, Z., Bagci, U. & Linguraru, M. G. (red.). Springer Science and Business Media Deutschland GmbH, s. 153-162 10 s. (Medical Image Learning with Limited and Noisy Data, Bind 13559).

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

    ID: 226561698