Zobrazeno 1 - 10
of 21
pro vyhledávání: '"Anvar, Kurmukov"'
Autor:
Paul M. Thompson, Anvar Kurmukov, Neda Jahanshad, Boris A. Gutman, Yulia I. Denisova, Daniel Moyer, Ayagoz Mussabaeva
Publikováno v:
Brain Connectivity
This work addresses the problem of constructing a unified, topologically optimal connectivity-based brain atlas. The proposed approach aggregates an ensemble partition from individual parcellations without label agreement, providing a balance between
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7c53d85fb3e80a7dccd81496349b7928
https://doi.org/10.1089/brain.2019.0722
https://doi.org/10.1089/brain.2019.0722
Autor:
Polina Druzhinina, Ekaterina Kondrateva, Arseny Bozhenko, Vyacheslav Yarkin, Maxim Sharaev, Anvar Kurmukov
Publikováno v:
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries ISBN: 9783031089985
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8ef6aa9eaaec99e4b36e6b45c82ecdb8
https://doi.org/10.1007/978-3-031-08999-2_15
https://doi.org/10.1007/978-3-031-08999-2_15
Publikováno v:
Neuro Oncol
BACKGROUND Despite advances in the characterization of genomic alterations in glioblastoma patient survival remains poor. The aim of this single center retrospective study was to estimate prognostic factors affecting to survival for optimizing person
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b82e8f8c13a0482ec8c9e6ba6a82e0a5
https://europepmc.org/articles/PMC8427338/
https://europepmc.org/articles/PMC8427338/
Autor:
Anvar, Kurmukov, Aleksandra, Dalechina, Talgat, Saparov, Mikhail, Belyaev, Svetlana, Zolotova, Andrey, Golanov, Anna, Nikolaeva
Publikováno v:
Studies in health technology and informatics. 281
In this article, we compare the performance of a state-of-the-art segmentation network (UNet) on two different glioblastoma (GB) segmentation datasets. Our experiments show that the same training procedure yields almost twice as bad results on the re
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::c80291e9793c5fa57f3978034d4f38a3
https://pubmed.ncbi.nlm.nih.gov/34042753
https://pubmed.ncbi.nlm.nih.gov/34042753
Autor:
Aleksandra Dalechina, Anna Nikolaeva, Talgat Saparov, Svetlana V. Zolotova, Mikhail Belyaev, Anvar Kurmukov, Andrey Golanov
Publikováno v:
MIE
In this article, we compare the performance of a state-of-the-art segmentation network (UNet) on two different glioblastoma (GB) segmentation datasets. Our experiments show that the same training procedure yields almost twice as bad results on the re
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::13e55aa7cf58d81ed8a6e8aa00dabd2b
https://doi.org/10.3233/shti210168
https://doi.org/10.3233/shti210168
Publikováno v:
2021 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology (USBEREIT).
Deep learning models performed very well in many medical image analysis tasks. However, the majority of these results had been obtained on carefully selected datasets. At the same time, the real clinical flow of Computed Tomography studies often cont
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::af765c1e9e7f6f64f5ea5c43bad76a13
https://doi.org/10.1109/usbereit51232.2021.9455083
https://doi.org/10.1109/usbereit51232.2021.9455083
Publikováno v:
ISBI
We present a method to simultaneously learn several linear discriminative models with explicit information sharing. We use TV-Ll-regularized Logistic Regression in conjunction with a Tikhonov regularization term expressing shared information across d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::619649bd2c8d0730997c27641b897642
https://doi.org/10.1109/isbi48211.2021.9434026
https://doi.org/10.1109/isbi48211.2021.9434026
Autor:
Mikhail Belyaev, Alexey Shevtsov, Mikhail Goncharov, Anvar Kurmukov, Boris Shirokikh, Alexander Solovev, Sergey Morozov, Maxim Pisov, I. A. Blokhin, Victor A. Gombolevskiy, Valeria Chernina
Publikováno v:
Medical Image Analysis
Graphical abstract
The current COVID-19 pandemic overloads healthcare systems, including radiology departments. Though several deep learning approaches were developed to assist in CT analysis, nobody considered study triage directly as a compute
The current COVID-19 pandemic overloads healthcare systems, including radiology departments. Though several deep learning approaches were developed to assist in CT analysis, nobody considered study triage directly as a compute
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::12e93da5f4f1695be58678d06e5af733
http://europepmc.org/articles/PMC8015379
http://europepmc.org/articles/PMC8015379
Publikováno v:
Deep Generative Models, and Data Augmentation, Labelling, and Imperfections ISBN: 9783030882099
DGM4MICCAI/DALI@MICCAI
DGM4MICCAI/DALI@MICCAI
Domain shift is one of the most salient challenges in medical computer vision. Due to immense variability in scanners’ parameters and imaging protocols, even images obtained from the same person and the same scanner could differ significantly. We a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::541aed0bf8411c0347215b2ee880ee07
https://doi.org/10.1007/978-3-030-88210-5_24
https://doi.org/10.1007/978-3-030-88210-5_24
Publikováno v:
Alzheimer's & Dementia. 16
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5a5e8d30dbdc1b870f1d32f1d96d7624
https://doi.org/10.1002/alz.046717
https://doi.org/10.1002/alz.046717