| Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge S Bakas, M Reyes, A Jakab, S Bauer, M Rempfler, A Crimi, RT Shinohara, ... arXiv preprint arXiv:1811.02629, 2018 | 1945 | 2018 |
| ISLES 2016 and 2017-benchmarking ischemic stroke lesion outcome prediction based on multispectral MRI S Winzeck, A Hakim, R McKinley, JA Pinto, V Alves, C Silva, M Pisov, ... Frontiers in neurology 9, 679, 2018 | 173 | 2018 |
| CT-Based COVID-19 triage: Deep multitask learning improves joint identification and severity quantification M Goncharov, M Pisov, A Shevtsov, B Shirokikh, A Kurmukov, I Blokhin, ... Medical image analysis 71, 102054, 2021 | 88 | 2021 |
| Ensembling neural networks for digital pathology images classification and segmentation A Pimkin, G Makarchuk, V Kondratenko, M Pisov, E Krivov, M Belyaev Image Analysis and Recognition: 15th International Conference, ICIAR 2018 …, 2018 | 35 | 2018 |
| Keypoints localization for joint vertebra detection and fracture severity quantification M Pisov, V Kondratenko, A Zakharov, A Petraikin, V Gombolevskiy, ... Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd …, 2020 | 26 | 2020 |
| Incorporating task-specific structural knowledge into CNNs for brain midline shift detection M Pisov, M Goncharov, N Kurochkina, S Morozov, V Gombolevskiy, ... Interpretability of Machine Intelligence in Medical Image Computing and …, 2019 | 24 | 2019 |
| Interpretable vertebral fracture quantification via anchor-free landmarks localization A Zakharov, M Pisov, A Bukharaev, A Petraikin, S Morozov, ... Medical Image Analysis 83, 102646, 2023 | 22 | 2023 |
| MRI augmentation via elastic registration for brain lesions segmentation E Krivov, M Pisov, M Belyaev Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries …, 2018 | 14 | 2018 |
| Brain tumor image retrieval via multitask learning M Pisov, G Makarchuk, V Kostjuchenko, A Dalechina, A Golanov, ... arXiv preprint arXiv:1810.09369, 2018 | 8 | 2018 |
| vox2vec: A framework for self-supervised contrastive learning of voxel-level representations in medical images M Goncharov, V Soboleva, A Kurmukov, M Pisov, M Belyaev International Conference on Medical Image Computing and Computer-Assisted …, 2023 | 6 | 2023 |
| Quantification of epicardial adipose tissue in low-dose computed tomography images M Goncharov, V Chernina, M Pisov, V Gombolevskiy, S Morozov, ... International Conference on Medical Imaging and Computer-Aided Diagnosis, 98-107, 2021 | 4 | 2021 |
| Ensembling neural networks for digital pathology images classification and segmentation G Makarchuk, V Kondratenko, M Pisov, A Pimkin, E Krivov, M Belyaev arXiv preprint arXiv:1802.00947, 2018 | 4 | 2018 |
| Neural networks ensembles for ischemic stroke lesion segmentation M Pisov, M Belyaev, E Krivov | 4 | 2017 |
| Epicardial fat tissue volumetry: comparison of semi-automatic measurement and the machine learning algorithm VY Chernina, ME Pisov, MG Belyaev, IV Bekk, KA Zamyatina, TA Korb, ... Kardiologiia 60 (9), 46-54, 2020 | 3 | 2020 |
| Fast lung localization in computed tomography by a 1D detection network V Proskurov, A Kurmukov, M Pisov, M Belyaev 2021 Ural Symposium on Biomedical Engineering, Radioelectronics and …, 2021 | 2 | 2021 |
| Diffeomorphic metric learning and template optimization for registration-based predictive models A Mussabayeva, M Pisov, A Kurmukov, A Kroshnin, Y Denisova, L Shen, ... Multimodal Brain Image Analysis and Mathematical Foundations of …, 2019 | 1 | 2019 |
| Ensembling Convolutional Neural Networks for Ischemic Stroke Lesion Segmentation Based on CT Images M Goncharov, M Pisov, M Belyaev ИТиС 2018, 85-89, 2018 | 1 | 2018 |
| Robust Curve Detection in Volumetric Medical Imaging via Attraction Field F Yaushev, D Nogina, V Samokhin, M Dugova, E Petrash, D Sevryukov, ... arXiv preprint arXiv:2408.01159, 2024 | | 2024 |
| The impact of deep learning aid on the workload and interpretation accuracy of radiologists on chest computed tomography: a cross-over reader study A Kurmukov, V Chernina, R Gareeva, M Dugova, E Petrash, O Aleshina, ... arXiv preprint arXiv:2406.08137, 2024 | | 2024 |
| Hierarchical Loss And Geometric Mask Refinement For Multilabel Ribs Segmentation A Leonov, A Zakharov, S Koshelev, M Pisov, A Kurmukov, M Belyaev arXiv preprint arXiv:2405.15500, 2024 | | 2024 |
