Bulat Ibragimov
Associate Professor, Associate Professor - Promotion Programme
Image Analysis, Computational Modelling and Geometry
Universitetsparken 1, 2100 København Ø
Member of:
- Published
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, In: Neurocomputing. 392, p. 181-188Research output: Contribution to journal › Journal article › Research › peer-review
- E-pub ahead of print
The Use of Machine Learning in Eye Tracking Studies in Medical Imaging: A Review
Ibragimov, Bulat & Mello-Thoms, C., 2024, (E-pub ahead of print) In: IEEE Journal of Biomedical and Health Informatics. 19 p.Research output: Contribution to journal › Journal article › Research › peer-review
- Published
Machine Learning for Image-Based Radiotherapy Outcome Prediction
Ibragimov, Bulat, 2023, Artificial Intelligence in Radiation Oncology and Biomedical Physics. Valdes, G. & Xing, L. (eds.). CRC Press, p. 25-52 28 p.Research output: Chapter in Book/Report/Conference proceeding › Book chapter › Research › peer-review
- Published
Deep learning for detection of clinical operations in robot-assisted percutaneous renal access
Ibragimov, Bulat, Zhen, J. & Ayvali, E., 2023, In: IEEE Access. 11, p. 90358-90366Research output: Contribution to journal › Journal article › Research › peer-review
- Published
A 178-clinical-center experiment of integrating AI solutions for lung pathology diagnosis
Ibragimov, Bulat, Arzamasov, K., Maksudov, B., Kiselev, S., Mongolin, A., Mustafaev, T., Ibragimova, D., Evteeva, K., Andreychenko, A. & Morozov, S., Dec 2023, In: Scientific Reports. 13, 1, 14 p., 1135.Research output: Contribution to journal › Journal article › Research › peer-review
- 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, , 2021, In: Scientific Reports. 11, 1, 12 p., 3246.Research output: Contribution to journal › Journal article › Research › peer-review
- Published
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, In: International Journal of Computer Assisted Radiology and Surgery. 15, 3, p. 425-436 12 p.Research output: Contribution to journal › Journal article › Research › peer-review
- Published
Gaze-Based Attention to Improve the Classification of Lung Diseases
Kholiavchenko, M., Pershin, I., Maksudov, B., Mustafaev, T., Yuan, Y. & Ibragimov, Bulat, 2022, Medical Imaging 2022: Image Processing. Colliot, O., Isgum, I., Landman, B. A. & Loew, M. H. (eds.). SPIE, 4 p. 120320C. (Progress in Biomedical Optics and Imaging - Proceedings of SPIE, Vol. 12032).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- Published
Automating cardiothoracic ratio measurements in chest X-rays
Kiselev, S., Maksudov, B., Mustafaev, T., Kuleev, R. & Ibragimov, Bulat, 2021, 2021 International Conference "Nonlinearity, Information and Robotics", NIR 2021. IEEE, 4 p.Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- Published
Physics-based loss and machine learning approach in application to non-Newtonian fluids flow modeling
Kornaeva, E., Kornaev, A., Fetisov, A., Stebakov, I. & Ibragimov, Bulat, 2022, 2022 IEEE Congress on Evolutionary Computation, CEC 2022 - Conference Proceedings. IEEE, 8 p.Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
ID: 219366603
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Developing and validating COVID-19 adverse outcome risk prediction models from a bi-national European cohort of 5594 patients
Research output: Contribution to journal › Journal article › Research › peer-review
Published -
23
downloads
Multi-landmark environment analysis with reinforcement learning for pelvic abnormality detection and quantification
Research output: Contribution to journal › Journal article › Research › peer-review
Published