Bulat Ibragimov
Associate Professor, Associate Professor - Promotion Programme
Image Analysis, Computational Modelling and Geometry
Universitetsparken 1, 2100 København Ø
Member of:
- 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
- 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
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
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
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
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, In: Medical Physics. 47, 8, p. 3721-3731Research 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
ID: 219366603
Most downloads
-
239
downloads
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