Bulat Ibragimov
Associate Professor, Associate Professor - Promotion Programme
Image Analysis, Computational Modelling and Geometry
Universitetsparken 1, 2100 København Ø
Member of:
- E-pub ahead of print
Building an AI Support Tool for Real-Time Ulcerative Colitis Diagnosis
Møller, Bjørn Leth, Lo, B. Z. S., Burisch, J., Bendtsen, Flemming, Vind, Ida, Ibragimov, Bulat & Igel, Christian, 2024, (E-pub ahead of print) In: KI - Künstliche Intelligenz. 8 p.Research output: Contribution to journal › Journal article › Research › peer-review
- Published
Changes in Radiologists’ Gaze Patterns Against Lung X-rays with Different Abnormalities: a Randomized Experiment
Pershin, I., Mustafaev, T., Ibragimova, D. & Ibragimov, Bulat, 2023, In: Journal of Digital Imaging. 36, 3, p. 767-775Research 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
Contrastive Learning Approach to Predict Radiologist's Error Based on Gaze Data
Pershin, I., Mustafaev, T. & Ibragimov, Bulat, 2023, 2023 IEEE Congress on Evolutionary Computation, CEC 2023. IEEEResearch output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- Published
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, In: IEEE Journal of Biomedical and Health Informatics. 25, 5, p. 1660-1672Research output: Contribution to journal › Journal article › 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
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
- Published
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, In: IEEE Transactions on Automation Science and Engineering. 17, 2, p. 574-583 10 p., 8842597.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
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. (eds.). Springer VS, p. 247-257 11 p. (Lecture Notes in Computer Science, Vol. 12396 LNCS).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