| 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 | 89 | 2021 |
| CrossMoDA 2021 challenge: Benchmark of cross-modality domain adaptation techniques for vestibular schwannoma and cochlea segmentation R Dorent, A Kujawa, M Ivory, S Bakas, N Rieke, S Joutard, B Glocker, ... Medical Image Analysis 83, 102628, 2023 | 51 | 2023 |
| First U-Net layers contain more domain specific information than the last ones B Shirokikh, I Zakazov, A Chernyavskiy, I Fedulova, M Belyaev Domain Adaptation and Representation Transfer, and Distributed and …, 2020 | 26 | 2020 |
| Universal loss reweighting to balance lesion size inequality in 3D medical image segmentation B Shirokikh, A Shevtsov, A Kurmukov, A Dalechina, E Krivov, ... Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd …, 2020 | 24 | 2020 |
| Anatomy of domain shift impact on U-Net layers in MRI segmentation I Zakazov, B Shirokikh, A Chernyavskiy, M Belyaev Medical Image Computing and Computer Assisted Intervention–MICCAI 2021: 24th …, 2021 | 23 | 2021 |
| Accelerating 3D medical image segmentation by adaptive small-scale target localization B Shirokikh, A Shevtsov, A Dalechina, E Krivov, V Kostjuchenko, ... Journal of Imaging 7 (2), 35, 2021 | 15 | 2021 |
| Sparse group inductive matrix completion I Nazarov, B Shirokikh, M Burkina, G Fedonin, M Panov arXiv preprint arXiv:1804.10653, 2018 | 15* | 2018 |
| Tumor delineation for brain radiosurgery by a convnet and non-uniform patch generation E Krivov, V Kostjuchenko, A Dalechina, B Shirokikh, G Makarchuk, ... Patch-Based Techniques in Medical Imaging: 4th International Workshop, Patch …, 2018 | 9 | 2018 |
| Deep learning for brain tumor segmentation in radiosurgery: prospective clinical evaluation B Shirokikh, A Dalechina, A Shevtsov, E Krivov, V Kostjuchenko, ... International MICCAI Brainlesion Workshop, 119-128, 2019 | 7 | 2019 |
| Systematic clinical evaluation of a deep learning method for medical image segmentation: radiosurgery application B Shirokikh, A Dalechina, A Shevtsov, E Krivov, V Kostjuchenko, ... IEEE Journal of Biomedical and Health Informatics 26 (7), 3037-3046, 2022 | 3 | 2022 |
| Redesigning out-of-distribution detection on 3d medical images A Vasiliuk, D Frolova, M Belyaev, B Shirokikh International Workshop on Uncertainty for Safe Utilization of Machine …, 2023 | 2 | 2023 |
| Limitations of out-of-distribution detection in 3d medical image segmentation A Vasiliuk, D Frolova, M Belyaev, B Shirokikh Journal of Imaging 9 (9), 191, 2023 | 2 | 2023 |
| Exploring structure-wise uncertainty for 3d medical image segmentation A Vasiliuk, D Frolova, M Belyaev, B Shirokikh International Conference on Medical Imaging and Computer-Aided Diagnosis, 15-26, 2022 | 2 | 2022 |
| Negligible effect of brain MRI data preprocessing for tumor segmentation E Kondrateva, P Druzhinina, A Dalechina, S Zolotova, A Golanov, ... arXiv preprint arXiv:2204.05278, 2022 | 2 | 2022 |
| Zero-Shot Domain Adaptation in CT Segmentation by Filtered Back Projection Augmentation T Saparov, A Kurmukov, B Shirokikh, M Belyaev arXiv preprint arXiv:2107.08543, 2021 | 2 | 2021 |
| WMH Segmentation Using an Adjusted DeepMedic Architecture and an Improved Learning Approach B Shirokikh, M Belyaev | 1 | 2019 |
| Solving Sample-Level Out-of-Distribution Detection on 3D Medical Images D Frolova, A Vasiliuk, M Belyaev, B Shirokikh arXiv preprint arXiv:2212.06506, 2022 | | 2022 |
| Adaptation to CT Reconstruction Kernels by Enforcing Cross-Domain Feature Maps Consistency S Shimovolos, A Shushko, M Belyaev, B Shirokikh Journal of Imaging 8 (9), 234, 2022 | | 2022 |
| Clinical evaluation of deep learning methods for brain tumor contouring A Dalechina, E Krivov, M Belyaev, V Kostjuchenko, B Shirokikh, ... EasyChair, 2019 | | 2019 |
Mikhail BeliaevCEO, AUMI AIVerified email at aumi.ai
