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Oleksii Bashkanov, M.Sc.Research AssistantFaculty of Computer ScienceOtto-von-Guericke University Magdeburg Office: G82-178Phone: ++49 391 67-57026 ed.ugvo@vonakhsab.iiskelo :liaM-E |
Scientific Publications
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| Bashkanov, O., Rak, M., Engelage, L., Hansen, C. (2024) |
| Augmenting Prostate MRI Dataset with Synthetic Volumetric Images from Zone-conditioned Diffusion Generative Model |
| MICCAI Workshop Deep Generative Models (DGM4MICCAI), accepted |
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| Gulamhussene, G., Bashkanov, O., Omari, J., Pech, M., Hansen, C., Rak, M. (2023) |
| Using Training Samples as Transitive Information Bridges in Predicted 4D MRI |
| MICCAI Workshop on Medical Image Learning with noisy and Limited Data (MILLanD), pp. 237-245 |
Paper 
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| Gulamhussene, G., Rak, M., Bashkanov, O., Joeres, F., Omari, J., Pech, M., Hansen, C. (2023) |
| Transfer-Learning is a Key Ingredient to Fast Deep Learning-Based 4D Liver MRI Reconstruction |
| Nature Scientific Reports, 13, pp. 11227 |
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| Bashkanov, O., Rak, M., Engelage, L., Lumiani, A., Muschter, R. Hansen, C. (2023) |
| Automatic Detection of Prostate Cancer Grades and Chronic Prostatitis in Biparametric MRI |
| Journal Computer Methods and Programs in Biomedicine, 239, pp. 107624 |
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| Bashkanov, O., Rak, M., Engelage, L., Hansen, C. (2023) |
| Automatic Patient-level Diagnosis of Prostate Disease with Fused 3D MRI and Tabular Clinical Data |
| Medical Imaging with Deep Learning (MIDL), pp. 128:1–14 |
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| Gulamhussene, G., Meyer, A., Rak, M., Bashkanov, O., Omari, J., Pech, M., Hansen, C. (2022) |
| Predicting 4D Liver MRI for MR-guided Interventions |
| Computerized Medical Imaging and Graphics, 101, pp. 102122 |
Download test data set  |
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| Meyer, A., Mehrtash, A., Rak, M., Bashkanov, O., Langbein, B., Ziaei, A., Kibel, A., Tempany, C., Hansen, C., Tokuda, J. (2021) |
| Domain Adaptation for Segmentation of Critical Structures for Prostate Cancer Therapy |
| Nature Scientific Reports, 11, pp. 11480 |
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| Bashkanov, O., Meyer, A., Schindele, D., Schostak, M., Toennies, K., Hansen, C., Rak, M. (2021) |
| Learning Multi-Modal Volumetric Prostate Registration with Weak Inter-Subject Spatial Correspondence |
| Proceedings of IEEE International Symposium on Biomedical Imaging (ISBI), Nice, France, pp. 1817-1821 |
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| Bashkanov, O., Saalfeld, P., Gunasekaran, H., Jabaraj, M., Preim, B., Huber, T., Huettl, F., Kneist, W., Hansen, C. (2019) |
| VR Multi-User Conference Room for Surgery Planning |
| Proceedings of the Annual Meeting of the German Society of Computer- and Robot-Assisted Surgery (CURAC), Reutlingen, Germany, in print |
Video