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Song, M., Cheng, J., Guo, S., Zhuang, Y., Tulupov, A., Fan, D., ... & Bao, J. (2024). Hollow magnetic vortex nanorings loaded with quercetin encapsulated in polydopamine: A high-performance, intelligent nanotheranostic platform for enhanced tumor imaging and dual thermal treatment. International Journal of Pharmaceutics, 660, 124335. https://doi.org/10.1016/j.ijpharm.2024.124335
Kirillov, K., Mikhailapov, D., Tulupov, A., & Berikov, V. (2024, September). Segmentation of 3D Non-Contrast CT Brain Images Using Transformer Neural Networks. In 2024 IEEE International Multi-Conference on Engineering, Computer and Information Sciences (SIBIRCON) (pp. 173-177). IEEE. https://doi.org/10.1109/SIBIRCON63777.2024.10758478
Luu, M. S. K., Tuchinov, B. N., Prokaeva, A. I., Korobko, D. S., Malkova, N. A., & Tulupov, A. A. (2024). Discovering predictive features of multiple sclerosis from clinically isolated syndrome with machine learning. Artificial Intelligence in Health, 1(4), 107-122. https://doi.org/10.36922/aih.4255
Makogon A.V., Gornostaeva A.M., Korostyshevskaya A.M. (2024). Рrenatal US- and MRdiagnostics of twin pregnancy with regressive complete hydatidiform mole and a coexisting live fetus. REJR; 14:144-154.
Khrushcheva, N. A., Kalgin, K. V., Savelov, A. A., Shurunova, A. V., Predtechenskaya, E. V., & Shtark, M. B. (2024). Changes in Clinical and Network Functional Connectivity Parameters in Motor Networks and Cerebellum Based on Resting-State Functional Magnetic Resonance Imaging Data in Patients with Post-Stroke Hemiparesis Receiving Interactive Brain Stimulation Neurotherapy. Annals of clinical and experimental neurology, 18(1), 33-43. https://doi.org/10.54101/ACEN.2024.1.4
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Dobshik, A. V., Verbitskiy, S. K., Pestunov, I. A., Sherman, K. M., Tulupov, A. A., & Berikov, V. B. (2023). Acute ischemic stroke lesion segmentation in non-contrast CT images using 3D convolutional neural networks. Компьютерная оптика, 47(5), 770-777. https://doi.org/10.18287/2412-6179-CO-1233
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Dyatlova A.A., Stankevich Y.A., Bogomyakova O.B., Vasilkiv L.V., Tulupov A.A. (2022). Possibilities of diffusion tensor imaging in the dynamic assessment of an ischemic stroke. Russian Electronic Journal of Radiology.- 2022.- Vol. 12.- № 3.- P. 29-38. https://doi.org/10.21569/2222-7415-2022-12-3-29-38
Mikhailapov, D., Tulupov, A., Alyamkin, S., & Berikov, V. (2022, July). Compression of Deep Neural Network for Acute Ischemic Stroke Segmentation. In 2022 Ural-Siberian Conference on Computational Technologies in Cognitive Science, Genomics and Biomedicine (CSGB) (pp. 240-245). IEEE. https://doi.org/10.1109/CSGB56354.2022.9865656
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Korostyshevskaya, A. M., Savelov, A. A., Abramova, V. D., & Shtark, M. B. (2022). Depression: magnetic resonance spectroscopy studies. Translational Medicine, 9(4), 20-32. https://doi.org/10.18705/2311-4495-2022-9-4-20-32
Berestov, V., Seleznev, P., Obedinskaya, N., Korostyshevskaya, A., Gofer, J., Bondarenko, I., ... & Orlov, K. (2022). Huge cerebral pial arteriovenous fistula in a newborn: illustrative case. Journal of Neurosurgery: Case Lessons, 4(16). https://doi.org/10.3171/CASE22294
Pnev, Sergey, Andrey Tulupov, and Vladimir Berikov. "Modified U-net with Different Attention Mechanisms for Acute Ischemic Stroke Segmentation using Non-Contrast CT." 2021 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology (USBEREIT). IEEE, 2021. https://doi.org/10.1109/USBEREIT51232.2021.9454963
Yan’kova, G. S., Cherevko, A. A., Khe, A. K., Bogomyakova, O. B., & Tulupov, A. A. (2021). Mathematical modeling of normal-pressure hydrocephalus at different levels of the brain geometry detalization. Journal of Applied Mechanics and Technical Physics, 62, 654-662. https://doi.org/10.1134/S0021894421040155
Bogomyakova, O., Vasilkiv, L., Stankevich, Y., Kim, V., & Tulupov, A. (2021). Hemo-and cerebrospinal fluid dynamics changes in patients with" overcrowded posterior cranial fossa" syndrome using MRI. European journal of neurology, 28, 646-647.
Yankova, G., Bogomyakova, O., & Tulupov, A. (2021). The glymphatic system and meningeal lymphatics of the brain: new understanding of brain clearance. Reviews in the Neurosciences, 32(7), 693-705. https://doi.org/10.1515/revneuro-2020-0106
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Kalmutskiy, Kirill, Andrey Tulupov, and Vladimir Berikov. "Recognition of tomographic images in the diagnosis of stroke." International Conference on Pattern Recognition. Cham: Springer International Publishing, 2021. https://doi.org/10.1007/978-3-030-68821-9_16
Bogomyakova, O. B., Vasilkiv, L. M., Stankevich, Y. A., Savelov, A. A., Korostyshevskaya, A. M., & Tulupov, A. A. (2020). Decompensation of chronic internal hydrocephalus in an adult patient. Zhurnal Voprosy Neirokhirurgii Imeni NN Burdenko, 84(6), 86-92. https://doi.org/10.17116/neiro20208406186
Rudnev, V., Melnikov, M., Savelov, A., Shtark, M., & Sokhadze, E. M. (2021). fMRI-EEG fingerprint regression model for motor cortex. NeuroRegulation, 8(3), 162-162. https://doi.org/10.15540/nr.8.3.162
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Stankevich, Y., Vasilkiv, L., Bogomyakova, O., & Tulupov, A. (2020). Assessment of Microcirculatory Changes in Normal-appearing White and Gray Matter of the Brain in Patients with Multiple Sclerosis by Perfusion MRI. Basic and Clinical Pharmacology and Toxicology, 127, 6-6.
Kasenova, B. G., Notov, I. K., Verdiev, R. V., Volobuev, D. I., Aliev, U. M., Mikailova, S. E., ... & Satinov, A. V. (2020). Current issues of pathogenesis, diagnostic visualization and methods of treatment peyronie’s disease. RUDN journal of medicine, 24, 9-25. https://doi.org/10.22363/2313-0245-2020-24-1-9-25
Nedel’ko V., Kozinets R., Tulupov A., Berikov V. (2020). Comparative Analysis of Deep Neural Network and Texture-Based Classifiers for Recognition of Acute Stroke using Non-Contrast CT Images. In 2020 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology (USBEREIT) (pp. 376-379). IEEE. https://doi.org/10.1109/USBEREIT48449.2020.9117784
Yan’kova, G. S., Cherevko, A. A., Khe, A. K., Bogomyakova, O. G. B., & Tulupov, A. A. (2020). Study of hydrocephalus using poroelastic models. Journal of Applied Mechanics and Technical Physics, 61, 14-24.
Cornejo, P., Feygin, T., Vaughn, J., Pfeifer, C. M., Korostyshevska, A., Patel, M., ... & Goncalves, L. F. (2020). Imaging of fetal brain tumors. Pediatric radiology, 50, 1959-1973.
Korostyshevskaya, A., Gornostaeva, A., Volkov, R., & Yarnykh, V. (2021). Iniencephaly: radiologic and pathomorphologic perinatal observation. Radiology Case Reports, 16, 201-204.
Mazhirina, K. G., Dzhafarova, O. A., Kozlova, L. I., Pervushina, O. N., Fedorov, A. A., Bliznyuk, M. V., ... & Shtark, M. B. (2020). The relationships between cortical activity while observing images featuring different degrees of ambiguity and ambiguity tolerance. Bulletin of Experimental Biology and Medicine, 169, 421-425. https://doi.org/10.1007/s10517-020-04900-y
A. Khe, V. Vanina, A. Cherevko, D. Parshin, A. Chebotnikov, A. Boiko, A. Tulupov. (2019). APPLICATION OF MAGNETIC RESONANCE IMAGING FOR STUDYING THE THREE-DIMENSIONAL FLOW STRUCTURE IN BLOOD VESSEL MODELS. Journal of Applied Mechanics and Technical Physics. Vol. 60.- № 2.- P. 257-264. https://doi.org/10.1134/S002189441902007
Yudkin, D. V., Grishchenko, I. V., Tulupov, A. A., Rymareva, Y. M., Maksimova, Y. V., & Shorina, A. R. (2019, October). Somatic instability of CGG repeats in the FMR1 gene is a factor in symptom severity in Fragile X syndrome patients. In EUROPEAN JOURNAL OF HUMAN GENETICS (Vol. 27, pp. 1387-1388). MACMILLAN BUILDING, 4 CRINAN ST, LONDON N1 9XW, ENGLAND: NATURE PUBLISHING GROUP.
Alexandra M. Korostyshevskaya, Irina Yu. Prihod’ko, Andrey A. Savelov, Vasily L. Yarnykh. (2019). Direct Comparison Between Apparent Diffusion Coefficient and Macromolecular Proton Fraction as Quantitative Biomarkers of the Human Fetal Brain Maturation. J. MAGN. RESON. IMAGING, 52-61. https://doi.org/10.1002/jmri.26635
Savelov, A. A., Shtark, M. B., Kozlova, L. I., Verevkin, E. G., Petrovskii, E. D., Pokrovskii, M. A., ... & Tsyrkin, G. M. (2019). Dynamics of interactions between cerebral networks derived from fMRI data and motor rehabilitation during stokes. Bulletin of Experimental Biology and Medicine, 166, 399-403.https://doi.org/10.1007/s10517-019-04359-6
Savelov, A. A., Shtark, M. B., Mel’nikov, M. E., Kozlova, L. I., Bezmaternykh, D. D., Verevkin, E. G., ... & Rudych, P. D. (2019). Prospects of synchronous fMRI-EEG recording as the basis for neurofeedback (exemplified on patient with stroke sequelae). Bulletin of experimental biology and medicine, 166, 390-393. https://doi.org/10.1007/s10517-019-04357-8
Savelov, A. A., Shtark, M. B., Mel’nikov, M. E., Kozlova, L. I., Bezmaternykh, D. D., Verevkin, E. G., ... & Rudych, P. D. (2019). Dynamics of fMRI and EEG parameters in a stroke patient assessed during a neurofeedback course focused on brodmann area 4 (M1). Bulletin of Experimental Biology and Medicine, 166, 394-398. https://doi.org/10.1007/s10517-019-04358-7
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