| 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 |
| 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 |
| Classification of normal and pathological brain networks based on similarity in graph partitions A Kurmukov, Y Dodonova, L Zhukov 2016 IEEE 16th International Conference on Data Mining Workshops (ICDMW …, 2016 | 13 | 2016 |
| Classifying phenotypes based on the community structure of human brain networks A Kurmukov, M Ananyeva, Y Dodonova, B Gutman, J Faskowitz, ... Graphs in Biomedical Image Analysis, Computational Anatomy and Imaging …, 2017 | 12 | 2017 |
| Machine learning application to human brain network studies: A kernel approach A Kurmukov, Y Dodonova, LE Zhukov Models, Algorithms, and Technologies for Network Analysis: NET 2016, Nizhny …, 2017 | 6* | 2017 |
| Topological modules of human brain networks are anatomically embedded: evidence from modularity analysis at multiple scales A Kurmukov, Y Dodonova, M Burova, A Mussabayeva, D Petrov, ... Computational Aspects and Applications in Large-Scale Networks: NET 2017 …, 2018 | 5 | 2018 |
| Optimizing connectivity-driven brain parcellation using ensemble clustering A Kurmukov, A Mussabaeva, Y Denisova, D Moyer, N Jahanshad, ... Brain Connectivity 10 (4), 183-194, 2020 | 3 | 2020 |
| 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 | 2 | 2023 |
| Do we really need all these preprocessing steps in brain MRI segmentation? E Kondrateva, P Druzhinina, A Kurmukov Medical Imaging with Deep Learning, 2022 | 2 | 2022 |
| 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 |
| Spatially adaptive morphometric knowledge transfer across neurodegenerative diseases Y Zhao, A Kurmukov, BA Gutman 2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI), 845-849, 2021 | 2 | 2021 |
| Zero-shot domain adaptation in ct segmentation by filtered back projection augmentation T Saparov, A Kurmukov, B Shirokikh, M Belyaev Deep Generative Models, and Data Augmentation, Labelling, and Imperfections …, 2021 | 2 | 2021 |
| Connectivity-driven brain parcellation via consensus clustering A Kurmukov, A Musabaeva, Y Denisova, D Moyer, B Gutman Connectomics in NeuroImaging: Second International Workshop, CNI 2018, Held …, 2018 | 2 | 2018 |
| Image registration and predictive modeling: learning the metric on the space of diffeomorphisms A Mussabayeva, A Kroshnin, A Kurmukov, Y Denisova, L Shen, S Cong, ... Shape in Medical Imaging: International Workshop, ShapeMI 2018, Held in …, 2018 | 2 | 2018 |
| 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 | 1 | 2022 |
| Neglectable effect of brain MRI data preprocessing for tumor segmentation. E Kondrateva, P Druzhinina, A Dalechina, B Shirokikh, M Belyaev, ... arXiv preprint arXiv:2204.05278, 2022 | 1 | 2022 |
| Challenges in Building of Deep Learning Models for Glioblastoma Segmentation: Evidence from Clinical Data. A Kurmukov, A Dalechina, T Saparov, M Belyaev, S Zolotova, A Golanov, ... MIE, 298-302, 2021 | 1 | 2021 |
| Shared imaging biomarkers across Alzheimer’s and Parkinson’s disease Y Zhao, A Kurmukov, J Goldman, BA Gutman 2020 Alzheimer's Association International Conference, 2020 | 1 | 2020 |
| Constraining disease progression models using subject specific connectivity priors A Kurmukov, Y Zhao, A Mussabaeva, B Gutman Connectomics in NeuroImaging: Third International Workshop, CNI 2019, Held …, 2019 | 1 | 2019 |
| 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 |
Boris GutmanAssistant Professor, Department of Biomedical Engineering, Illinois Institute of TechnologyEmail verificata su iit.edu
