Bulat Ibragimov

Bulat Ibragimov

Tenure Track Adjunkt


Udgivelsesår:
  1. 2021
  2. Udgivet

    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, Christina, Igel, Christian, Boomsma, Wouter, Krause, Oswin, Lorenzen, Stephan Sloth, Selvan, Raghav, Petersen, Janne, Nyeland, M. E., Ankarfeldt, Mikkel Zöllner, Virenfeldt, G. M., Winther-Jensen, M., Linneberg, Allan René, Ghazi, M. M., Detlefsen, N., Lauritzen, Andreas, Smith, Abraham George, 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, I: Scientific Reports. 11, 1, 12 s., 3246.

    Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

  3. Udgivet

    Deep Learning for Diagnosis and Segmentation of Pneumothorax: The Results on The Kaggle Competition and Validation Against Radiologists

    Tolkachev, A., Sirazitdinov, I., Kholiavchenko, M., Mustafaev, T. & Ibragimov, Bulat, 2021, I: IEEE Journal of Biomedical and Health Informatics. 25, 5, s. 1660-1672

    Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

  4. 2020
  5. Udgivet

    Joint Spatial-Wavelet Dual-Stream Network for Super-Resolution

    Chen, Z., Guo, X., Yang, C., Ibragimov, Bulat & Yuan, Y., 2020, Medical Image Computing and Computer Assisted Intervention – MICCAI 2020 - 23rd International Conference, Proceedings. Martel, A. L., Abolmaesumi, P., Stoyanov, D., Mateus, D., Zuluaga, M. A., Zhou, S. K., Racoceanu, D. & Joskowicz, L. (red.). Springer VS, s. 184-193 10 s. (Lecture Notes in Computer Science, Bind 12265 LNCS).

    Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

  6. Udgivet

    Automated hepatobiliary toxicity prediction after liver stereotactic body radiation therapy with deep learning-based portal vein segmentation

    Ibragimov, Bulat, Toesca, D. A. S., Chang, D. T., Yuan, Y., Koong, A. C. & Xing, L., 2020, I: Neurocomputing. 392, s. 181-188

    Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

  7. Udgivet

    Deep learning for identification of critical regions associated with toxicities after liver stereotactic body radiation therapy

    Ibragimov, Bulat, Toesca, D. A. S., Chang, D. T., Yuan, Y., Koong, A. C., Xing, L. & Vogelius, Ivan R. , 2020, I: Medical Physics. 47, 8, s. 3721-3731

    Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

  8. Udgivet

    Contour-aware multi-label chest X-ray organ segmentation

    Kholiavchenko, M., Sirazitdinov, I., Kubrak, K., Badrutdinova, R., Kuleev, R., Yuan, Y., Vrtovec, T. & Ibragimov, Bulat, 2020, I: International Journal of Computer Assisted Radiology and Surgery. 15, 3, s. 425-436 12 s.

    Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

  9. Udgivet

    Low dose 4D-CT super-resolution reconstruction via inter-plane motion estimation based on optical flow

    Liu, H., Lin, Y., Ibragimov, Bulat & Zhang, C., 2020, I: Biomedical Signal Processing and Control. 62, 12 s., 102085.

    Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

  10. Udgivet

    Evaluation of Deep Learning Methods for Bone Suppression from Dual Energy Chest Radiography

    Sirazitdinov, I., Kubrak, K., Kiselev, S., Tolkachev, A., Kholiavchenko, M. & Ibragimov, Bulat, 2020, Artificial Neural Networks and Machine Learning – ICANN 2020 - 29th International Conference on Artificial Neural Networks, Proceedings. Farkaš, I., Masulli, P. & Wermter, S. (red.). Springer VS, s. 247-257 11 s. (Lecture Notes in Computer Science, Bind 12396 LNCS).

    Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

  11. Udgivet

    Auto-segmentation of organs at risk for head and neck radiotherapy planning: From atlas-based to deep learning methods

    Vrtovec, T., Močnik, D., Strojan, P., Pernuš, F. & Ibragimov, Bulat, 2020, I: Medical Physics. 47, 9, s. e929-e950

    Publikation: Bidrag til tidsskriftReviewForskningfagfællebedømt

  12. Udgivet

    Densely Connected Neural Network with Unbalanced Discriminant and Category Sensitive Constraints for Polyp Recognition

    Yuan, Y., Qin, W., Ibragimov, Bulat, Zhang, G., Han, B., Meng, M. Q. H. & Xing, L., 2020, I: IEEE Transactions on Automation Science and Engineering. 17, 2, s. 574-583 10 s., 8842597.

    Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

  13. 2019
  14. Udgivet

    Neural Networks for Deep Radiotherapy Dose Analysis and Prediction of Liver SBRT Outcomes

    Ibragimov, Bulat, Toesca, D. A. S., Yuan, Y., Koong, A. C., Chang, D. T. & Xing, L., 2019, I: IEEE Journal of Biomedical and Health Informatics. 23, 5, s. 1821-1833 13 s., 8664101.

    Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

ID: 219366603