Mostafa Mehdipour Ghazi

Mostafa Mehdipour Ghazi

Assistant Professor

ORCID: 0000-0002-8473-281X

Publication year:
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1 - 16 out of 16Page size: 500
  1. 2024
  2. Published

    CARRNN: A Continuous Autoregressive Recurrent Neural Network for Deep Representation Learning From Sporadic Temporal Data

    Mehdipour Ghazi, Mostafa, Sørensen, L., Ourselin, S. & Nielsen, Mads, 2024, In: IEEE Transactions on Neural Networks and Learning Systems. 35, 1, p. 792-802

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

  3. Published

    Comparative analysis of multimodal biomarkers for amyloid-beta positivity detection in Alzheimer's disease cohorts

    Mehdipour Ghazi, Mostafa, Selnes, P., Timón-Reina, S., Tecelão, S., Ingala, S., Bjørnerud, A., Kirsebom, B. E., Fladby, T. & Nielsen, Mads, 2024, In: Frontiers in Aging Neuroscience. 16, 1345417.

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

  4. Published

    Heterogeneous Learning for Brain Lesion Segmentation, Detection, and Classification

    Llambias, Sebastian Nørgaard, Nielsen, Mads & Mehdipour Ghazi, Mostafa, 2024, Proceedings of the 5th Northern Lights Deep Learning Conference ({NLDL}). PMLR, p. 138-144 (Proceedings of Machine Learning Research, Vol. 233).

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

  5. 2023
  6. Published

    Active Transfer Learning for 3D Hippocampus Segmentation

    Wu, J., Kang, Zhongfeng, Llambias, Sebastian Nørgaard, Mehdipour Ghazi, Mostafa & Nielsen, Mads, 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. (eds.). Springer, p. 224-234 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 14307 LNCS).

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

  7. Published

    Deep Learning-Based Assessment of Cerebral Microbleeds in COVID-19

    Ferrer, N. R., Vendela Sagar, M., Klein, Kiril Vadimovic, Kruuse, Christina Rostrup, Nielsen, Mads & Mehdipour Ghazi, Mostafa, 2023, 2023 IEEE International Symposium on Biomedical Imaging, ISBI 2023. IEEE Computer Society Press, p. 1-4 4 p. (Proceedings - International Symposium on Biomedical Imaging, Vol. 2023-April).

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

  8. Published

    GAN-ISI: Generative Adversarial Networks Image Source Identification Using Texture Analysis

    Ghazi, M. M. & Mehdipour Ghazi, Mostafa, 2023, In: CEUR Workshop Proceedings. 3497, p. 1588-1595

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

  9. Published

    Partial feedback online transfer learning with multi-source domains

    Kang, Zhongfeng, Nielsen, Mads, Yang, B. & Mehdipour Ghazi, Mostafa, 2023, In: Information Fusion. 89, p. 29-40

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

  10. Published

    Power and distribution of evoked gamma oscillations in brain aging and cognitive performance

    Bakhtiari, Aftab, Petersen, J., Urdanibia-Centelles, O., Mehdipour Ghazi, Mostafa, Fagerlund, Birgitte, Mortensen, Erik Lykke, Osler, Merete, Lauritzen, Martin & Benedek, Krisztina, 2023, In: GeroScience. 45, p. 1523–1538 16 p.

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

  11. 2022
  12. Published

    FAST-AID Brain: Fast and Accurate Segmentation Tool using Artificial Intelligence Developed for Brain

    Mehdipour Ghazi, Mostafa & Nielsen, Mads, 2022, arXiv.org, 18 p.

    Research output: Working paper › Preprint › Research

  13. 2021
  14. Published

    CARRNN: A Continuous Autoregressive Recurrent Neural Network for Deep Representation Learning from Sporadic Temporal Data

    Mehdipour Ghazi, Mostafa, Sørensen, L., Ourselin, S. & Nielsen, Mads, 2021, arXiv.org, 11 p.

    Research output: Working paper › Preprint › Research

  15. Published

    Developing and validating COVID-19 adverse outcome risk prediction models from a bi-national European cohort of 5594 patients

    Jimenez-Solem, E., Petersen, T. S., Hansen, C., Hansen, C., Lioma, C., Igel, C., Boomsma, W., Krause, O., Lorenzen, S., Selvan, R., Petersen, J., Nyeland, M. E., Ankarfeldt, M. Z., Virenfeldt, G. M., Winther-Jensen, M., Linneberg, A., Ghazi, M. M., Detlefsen, N., Lauritzen, A. D., Smith, A. G. & 15 others, de Bruijne, Marleen, Ibragimov, Bulat, Petersen, Jens, Lillholm, Martin, Middleton, Jon Anthony, Mogensen, S. H., Thorsen-Meyer, H., Perner, Anders, Helleberg, M., Kaas-Hansen, Benjamin Skov, Bonde, M., Bonde, A., Pai, A., Nielsen, Mads & Sillesen, Martin Hylleholt, 2021, In: Scientific Reports. 11, 1, 12 p., 3246.

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

  16. Published

    Robust parametric modeling of Alzheimer's disease progression

    Mehdipour Ghazi, Mostafa, Nielsen, Mads, Pai, A., Modat, M., Jorge Cardoso, M., Ourselin, S. & Sørensen, L., 2021, In: NeuroImage. 225, 12 p., 117460.

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

  17. 2019
  18. Published

    MRI Biomarkers Improve Disease Progression Modeling-Based Prediction of Cognitive Decline

    Mehdipour Ghazi, Mostafa, Nielsen, Mads, Pai, A. S. U., Modat , M., Cardoso , J., Ourselin, S. & Sorensen, L., 2019. 1 p.

    Research output: Contribution to conference › Conference abstract for conference › Research

  19. Published

    On the initialization of long short-term memory networks

    Mehdipour Ghazi, Mostafa, Nielsen, Mads, Pai, A., Modat, M., Cardoso, M. J., Ourselin, S. & Sørensen, L., 2019, Neural Information Processing - 26th International Conference, ICONIP 2019, Proceedings. Gedeon, T., Wong, K. W. & Lee, M. (eds.). Springer VS, p. 275-286 12 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 11953 LNCS).

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

  20. Published

    Training recurrent neural networks robust to incomplete data: application to Alzheimer’s disease progression modeling

    Mehdipour Ghazi, Mostafa, Nielsen, Mads, Pai, A. S. U., Cardoso, M. J., Modat, M., Ourselin, S. & Sørensen, L., 2019, In: Medical Image Analysis. 53, p. 39-46

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

  21. 2018
  22. Published

    Robust training of recurrent neural networks to handle missing data for disease progression modeling

    Mehdipour Ghazi, Mostafa, Nielsen, Mads, Pai, A. S. U., Cardoso, M. J., Modat, M., Ourselin, S. & Sørensen, L., 2018. 9 p.

    Research output: Contribution to conference › Paper › Research

ID: 204203641