Zobrazeno 1 - 10
of 1 055
pro vyhledávání: '"A. Golanov"'
Autor:
Kondrateva, Ekaterina, Druzhinina, Polina, Dalechina, Alexandra, Zolotova, Svetlana, Golanov, Andrey, Shirokikh, Boris, Belyaev, Mikhail, Kurmukov, Anvar
Magnetic resonance imaging (MRI) data is heterogeneous due to differences in device manufacturers, scanning protocols, and inter-subject variability. A conventional way to mitigate MR image heterogeneity is to apply preprocessing transformations such
Externí odkaz:
http://arxiv.org/abs/2204.05278
Autor:
Kondrateva, Ekaterina, Druzhinina, Polina, Dalechina, Alexandra, Zolotova, Svetlana, Golanov, Andrey, Shirokikh, Boris, Belyaev, Mikhail, Kurmukov, Anvar
Publikováno v:
In Biomedical Signal Processing and Control October 2024 96 Part A
Publikováno v:
IEEE Open Journal of Intelligent Transportation Systems, Vol 5, Pp 174-185 (2024)
Despite all efforts to enhance safety, construction sites remain a major location for traffic accidents. Short-term construction sites, in particular, face limitations in implementing extensive safety measures due to their condensed timelines. This p
Externí odkaz:
https://doaj.org/article/2cb1f7a3405c4f2aa4b827a1fbbfcf6e
Autor:
Shirokikh, Boris, Dalechina, Alexandra, Shevtsov, Alexey, Krivov, Egor, Kostjuchenko, Valery, Durgaryan, Amayak, Galkin, Mikhail, Golanov, Andrey, Belyaev, Mikhail
We systematically evaluate a Deep Learning (DL) method in a 3D medical image segmentation task. Our segmentation method is integrated into the radiosurgery treatment process and directly impacts the clinical workflow. With our method, we address the
Externí odkaz:
http://arxiv.org/abs/2108.09535
Autor:
Shirokikh, Boris, Shevtsov, Alexey, Kurmukov, Anvar, Dalechina, Alexandra, Krivov, Egor, Kostjuchenko, Valery, Golanov, Andrey, Belyaev, Mikhail
Target imbalance affects the performance of recent deep learning methods in many medical image segmentation tasks. It is a twofold problem: class imbalance - positive class (lesion) size compared to negative class (non-lesion) size; lesion size imbal
Externí odkaz:
http://arxiv.org/abs/2007.10033
Autor:
Yury Yu. Trunin, Andrey V. Golanov, Alexander N. Konovalov, Igor N. Pronin, Leonid B. Likhterman, Ruslan I. Zagirov
Publikováno v:
Клинический разбор в общей медицине, Vol 4, Iss 5, Pp 25-31 (2023)
The paper reports the analysis of the stereotactic irradiation outcomes in 430 patients with pilocytic astrocytomas (PAs), who underwent treatment in 2005–2018. The comprehensive approach to treatment of patients with intracranial pilocytic astrocy
Externí odkaz:
https://doaj.org/article/6c014e9ad1d6407dbe46b2c2340e3dc1
Publikováno v:
Клинический разбор в общей медицине, Vol 4, Iss 5, Pp 37-44 (2023)
The improvement of neuroimaging methods and introduction of the principles of microsurgery and radiosurgery involving the use of the Gamma Knife and CyberKnife systems into clinical practice have significantly changed the treatment outcomes in patien
Externí odkaz:
https://doaj.org/article/7f045f382123490fbe45c776a5ff3059
Autor:
Pimkin, Artem, Samoylenko, Alexander, Antipina, Natalia, Ovechkina, Anna, Golanov, Andrey, Dalechina, Alexandra, Belyaev, Mikhail
Recent CT Metal Artifacts Reduction (MAR) methods are often based on image-to-image convolutional neural networks for adjustment of corrupted sinograms or images themselves. In this paper, we are exploring the capabilities of a multi-domain method wh
Externí odkaz:
http://arxiv.org/abs/1911.05530
Autor:
Shirokikh, Boris, Dalechina, Alexandra, Shevtsov, Alexey, Krivov, Egor, Kostjuchenko, Valery, Durgaryan, Amayak, Galkin, Mikhail, Osinov, Ivan, Golanov, Andrey, Belyaev, Mikhail
Stereotactic radiosurgery is a minimally-invasive treatment option for a large number of patients with intracranial tumors. As part of the therapy treatment, accurate delineation of brain tumors is of great importance. However, slice-by-slice manual
Externí odkaz:
http://arxiv.org/abs/1909.02799
Autor:
Pisov, Maxim, Makarchuk, Gleb, Kostjuchenko, Valery, Dalechina, Alexandra, Golanov, Andrey, Belyaev, Mikhail
Classification-based image retrieval systems are built by training convolutional neural networks (CNNs) on a relevant classification problem and using the distance in the resulting feature space as a similarity metric. However, in practical applicati
Externí odkaz:
http://arxiv.org/abs/1810.09369