Ilyasova, Natalya Y.

2023

• 1 Ilyasova N.Y., Demin N.S. Systems for Recognition and Intelligent Analysis of Biomedical Images // Pattern Recognition and Image Analysis 2023. — Vol. 33. Issue 4. № 4. — P. 1142-1167
• 2 Demin N.S., Ilyasova N.Yu., Paringer R.A. Automatic Selection of the Optimal Zone for Laser Exposure According to the Fundus Images for Laser Coagulation // Journal of Biomedical Photonics and Engineering 2023. — Vol. 9. Issue 4. № 4.
• 3 Ilyasova N.Yu., Demin N.S., Surovcev E.N. etc. Possibilities of MRI Texture Analysis of Brain Images in Differential Diagnosis of Primary Extra-Axial Tumors // Journal of Biomedical Photonics and Engineering 2023. — Vol. 9. Issue 4. № 4.
• 4 Demin N.S., Ilyasova N.Y., Paringer R.A. etc. Application of artificial intelligence in ophthalmology for solving the problem of semantic segmentation of fundus images // Computer Optics 2023. — Vol. 47. Issue 5. № 5. — P. 824-831
• 5 Ilyasova N., Demin N. Application of Artificial Intelligence in Ophthalmology for Coagulate Map Formation to Carry Out Laser Eye Treatment // Lecture Notes in Computer Science. — 2023. — Vol. 13644 LNCS. — P. 387-402

2011

• 1 Ilyasova N.Y., Kupriyanov A.V., Ustinov A.V. Intraocular foreign body characteristics study on the basis of skull radiographical images analysis // Computer Optics 2011. — Vol. 35. Issue 2. — P. 268-274

1997

• 1 Iliasova N.Yu., Ustinov A.V., Bystrov N.D. etc. Evaluating the geometrical parameters of images of atomization jet cross-section in diagnostics of diesel injectors // Proceedings of SPIE - The International Society for Optical Engineering. — 1997. — Vol. 3348. — P. 308-315
• 2 Iliasova N.Yu., Ustinov A.V., Branchevsky S.L. etc. Methods for estimating geometric parameters of retinal vessels using diagnostic images of fundus // Proceedings of SPIE - The International Society for Optical Engineering. — 1997. — Vol. 3348. — P. 316-325

2000

• 1 Ilyasova, NY, Baranov VG, Ustinov AV etc. Expert evaluation of retinal pathologies using digital image analysis // ELECTRO-OPTICS AND MICROELECTRONICS, PROCEEDINGS. — 2000. — Vol. 14. — P. 95-98

2002

• 1 Soifer V.A., Kotlyar V.V., Khonina S.N. etc. Measuring the geometric parameters using image processing and diffractive optics methods // Proceedings of SPIE - The International Society for Optical Engineering. — 2002. — Vol. 4900. Issue 2. — P. 996-1006

2004

• 1 Ilyasova N.Y., Kupriyanov A.V., Ananin M.A. etc. Measuring biomechanical characteristics of blood vessels for early diagnostics of vascular retinal pathologies // Lecture Notes in Computer Science. — 2004. — Vol. 3217. Issue 1 PART 2. — P. 251-258

2005

• 1 Kupriyanov A., Ilyasova N., Malapheyev A. Diagnostic analysis using textural features of the lachrymal fluid crystal images // 13th European Signal Processing Conference, EUSIPCO 2005. — 2005. — P. 436-439

2006

• 1 Yatul'chik V.V., Il'yasova N.Yu. Methods for formation of features of tree-like structures on fundus images // Pattern Recognition and Image Analysis 2006. — Vol. 16. Issue 1. — P. 123-126

2007

• 1 Anan'in M.A., Il'yasova N.Yu., Kupriyanov A.V. Estimating directions of optic disk blood vessels in retinal images // Pattern Recognition and Image Analysis 2007. — Vol. 17. Issue 4. — P. 523-526
• 2 Kupriyanov A.V., Ilyasova N.Yu., Ananin M.A. Geometrical parameters estimation of the retina images for blood vessels pathology diagnostics // European Signal Processing Conference. — 2007. — P. 1251-1254

2009

• 1 Ilyasova N.Y., Kazansky N.L., Korepanov A.O. etc. Computer technology for the spatial reconstruction of the coronary vesels structure from angigographic projections // Computer Optics 2009. — Vol. 33. Issue 3. — P. 281-317
• 2 Korepanov A.O., Ilyasova N.Y., Kupriyanov A.V. A method of the wavelet transformation for estimation of geometrical parameters upon the diagnostic images // Optical Memory and Neural Networks (Information Optics) 2009. — Vol. 18. Issue 4. — P. 343-348

2013

• 1 Ilyasova N.Y. Methods for digital analysis of human vascular system. Literature review // Computer Optics 2013. — Vol. 37. Issue 4. — P. 511-535

2022

• 1 Ilyasova N.Y., Demin N.S. Application of Artificial Intelligence in Ophthalmology for the Diagnosis and Treatment of Eye Diseases // Pattern Recognition and Image Analysis 2022. — Vol. 32. Issue 3. № 3. — P. 477-482
• 2 Mukhin A.V., Kilbas I.A., Paringer R.A. etc. A method for balancing a multi-labeled biomedical dataset // INTEGRATED COMPUTER-AIDED ENGINEERING 2022. — Vol. 29. Issue 2. — P. 209-225
• 3 Ilyasova N.Yu., Kirsh D.V., Demin N.S. Decision-making support system for the personalization of retinal laser treatment in diabetic retinopathy // Computer Optics 2022. — Vol. 46. Issue 5. № 5. — P. 774-782
• 4 Ilyasova N.Y., Paringer R.A., Shirokanev A. S. etc. An Approach to Semantic Segmentation of Retinal Images Using Deep Neural Networks for Mapping Laser Exposure Zones for the Treatment of Diabetic Macular Edema // Lecture Notes in Networks and Systems. — 2022. — Vol. 330 LNNS. — P. 106-116
• 5 Paringer R.A., Mukhin A.V., Ilyasova N.Y. etc. Neural network application for semantic segmentation of fundus // Computer Optics 2022. — Vol. 46. Issue 4. № 4. — P. 596-602
• 6 Mashkov D.V., Ilyasova N., Demin N. Investigation of segmentation methods for highlighting areas of interests on lung X-rays // 2022 8th International Conference on Information Technology and Nanotechnology, ITNT 2022. — 2022. —
• 7 Demin N., Ilyasova N. Semantic segmentation of lung radiographs using U-net type neural network // 2022 8th International Conference on Information Technology and Nanotechnology, ITNT 2022. — 2022. —

2014

• 1 Ilyasova N.Y. Estimating the geometric features of a 3D vascular structure // Computer Optics 2014. — Vol. 38. Issue 3. — P. 529-538
• 2 Ilyasova N.Y. Computer systems for geometrical analysis of blood vessels diagnostic images // Optical Memory and Neural Networks (Information Optics) 2014. — Vol. 23. Issue 4. — P. 278-286
• 3 Ilyasova N.Y., Kupriyanov A.V. Simulation of images generated by the interaction of low energy X-ray radiation with materials // Pattern Recognition and Image Analysis 2014. — Vol. 24. Issue 3. — P. 452-456
• 4 Ilyasova N.Y., Kupriyanov A.V., Paringer R.A. Formation of features for improving the quality of medical diagnosis based on discriminant analysis methods // Computer Optics 2014. — Vol. 38. Issue 4. — P. 851-855

2015

• 1 Ilyasova N.Y. Evaluation of geometric characteristics of the spatial structure of vessels // Pattern Recognition and Image Analysis 2015. — Vol. 25. Issue 4. — P. 621-625
• 2 Ilyasova N.Y., Kupriyanov A.V., Paringer R.A. The discriminant analysis application to refine the diagnostic features of blood vessels images // Optical Memory and Neural Networks (Information Optics) 2015. — Vol. 24. Issue 4. — P. 309-313
• 3 Kupriyanov A., Ilyasova N., Paringer R.A. Dendritic crystallogram images classification // Journal of Biomedical Photonics & Engineering 2015. — № Vol. 1, No 2. — P. 135-138
• 4 Ilyasova N.Y. Methods to evaluate the three-dimensional features of blood vessels // Optical Memory and Neural Networks (Information Optics) 2015. — Vol. 24. Issue 1. — P. 36-47
• 5 Ilyasova N.Yu., Kupriyanov A.V. The Big Data mining to improve medical diagnostics quality // CEUR Workshop Proceedings. — 2015. — Vol. 1490. — P. 346-354

2016

• 1 Ilyasova N.Yu., Paringer R.A., Kupriyanov A.V. etc. The effective features formation for the identification of regions of interest in a fundus images // CEUR Workshop Proceedings. — 2016. — Vol. 1638. — P. 788-795
• 2 Ilyasova N.Yu., Abulkhanov D.A., Kupriyanov A.V. etc. Evaluation of aberrations in the optical system of the human eye based on the spatial spectrum of a diagnostic image // CEUR Workshop Proceedings. — 2016. — Vol. 1638. — P. 39-48
• 3 Ilyasova N., Paringer R., Kupriyanov A. Regions of interest in a fundus image selection technique using the discriminative analysis methods // International Conference on Computer Vision and Graphics, ICCVG 2016. — 2016. — Vol. 9972 LNCS. — P. 408-417

2017

• 1 Ustinov A.V., Ilyasova N.Yu., Demin N.S. An algorithm for correcting X-ray image distortions caused by central projection // CEUR Workshop Proceedings. — 2017. — Vol. 1900. — P. 10-15
• 2 Ilyasova N., Shirokanev A. S. , Kirsh D. etc. Development of coagulate map formation algorithms to carry out treatment by laser coagulation // Procedia Engineering. — 2017. — Vol. 201. — P. 271-279
• 3 Surnin O.L., Sitnikov P.V., Ivaschenko A. V. etc. Big data incorporation based on open services provider for distributed enterprises // CEUR Workshop Proceedings. — 2017. — Vol. 1903. — P. 42-47
• 4 Ilyasova N., Paringer R., Shirokanev A. S. etc. A smart feature selection technique for object localization in ocular fundus images with the aid of color subspaces // Procedia Engineering. — 2017. — Vol. 201. — P. 736-745
• 5 Ilyasova N., Paringer R., Kupriyanov A. etc. Intelligent feature selection technique for segmentation of fundus images // 7th International Conference on Innovative Computing Technology, INTECH 2017. — 2017. — P. 138-143
• 6 Ilyasova N., Kirsh D., Paringer R. etc. Coagulate map formation algorithms for laser eye treatment // 2017 3rd International Conference on Frontiers of Signal Processing, ICFSP 2017. — 2017. — P. 120-124
• 7 Ilyasova N.Yu., Baisova A.S., Kupriyanov A.V. Development and study of methods for estimating retinal vessel parameters using a modified local fan transform // CEUR Workshop Proceedings. — 2017. — Vol. 1901. — P. 92-98

2018

• 1 Ilyasova N.Y., Shirokanev A. S. , Kupriyanov A.V. etc. Methods of Intellectual Analysis in Medical Diagnostic Tasks Using Smart Feature Selection // Pattern Recognition and Image Analysis 2018. — Vol. 28. Issue 4. — P. 637-645
• 2 Ilyasova N.Yu., Shirokanev A. S. , Paringer R.A. etc. A modified technique for smart textural feature selection to extract retinal regions of interest using image pre-processing // Journal of Physics: Conference Series. — 2018. — Vol. 1096. Issue 1.
• 3 Shirokanev A. S. , Kirsh D.V., Ilyasova N.Y. etc. Investigation of algorithms for coagulate arrangement in fundus images // Computer Optics 2018. — Vol. 42. Issue 4. — P. 712-721
• 4 Khorin P.A., Ilyasova N.Yu., Paringer R.A. Выделение информативных признаков на основе коэффициентов полиномов Цернике при различных патологиях роговицы человеческого глаза // Computer Optics 2018. — Vol. 42. № 1. — P. 159-166
• 5 Ivaschenko A. V. , Ilyasova N.Yu., Khorina A.A. etc. Integration issues of big data analysis on social networks // CEUR Workshop Proceedings. — 2018. — Vol. 2212. — P. 248-254
• 6 Khorin P.A., Ilyasova N.Y., Paringer R.A. Informative feature selection based on the zernike polynomial coefficients for various pathologies of the human eye cornea // Computer Optics 2018. — Vol. 42. Issue 1. — P. 159-166
• 7 Ilyasova N., Kupriyanov A., Paringer R. etc. Particular Use of BIG DATA in Medical Diagnostic Tasks // Pattern Recognition and Image Analysis 2018. — Vol. 28. Issue 1. — P. 114-121
• 8 Shirokanev A.S., Kirsh D.V., Ilyasova N.Yu. etc. Исследование алгоритмов расстановки коагулятов на изображение глазного дна // Computer Optics 2018. — Vol. 42. № 4. — P. 712-721

2019

• 1 Ilyasova N.Y., Shirokanev A. S. , Kupriyanov A.V. etc. Technology of intellectual feature selection for a system of automatic formation of a coagulate plan on retina // Computer Optics 2019. — Vol. 43. Issue 2. — P. 304-315
• 2 Ilyasova N., Shirokanev A. S. , Demin N. etc. Graph-based segmentation for diabetic macular edema selection in OCT images // 2019 5th International Conference on Frontiers of Signal Processing, ICFSP 2019. — 2019. — P. 77-81
• 3 Ilyasova N.Y., Shikhevich V. A. , Shirokanev A. S. CUDA parallel programming technology application for analysis of big biomedical data based on computation of effectiveness features // Journal of Physics: Conference Series. — 2019. — Vol. 1368. Issue 5.
• 4 Ilyasova N.Y., Shirokanev A. S. , Klimov I. A. Application of convolution neural networks in eye fundus image analysis // CEUR Workshop Proceedings. — 2019. — Vol. 2416. — P. 74-79
• 5 Ilyasova N.Y., Shirokanev A. S. , Demin N.S. etc. Localization of diabetic macular edema areas via graph-based segmentation of OCT retinal images // Journal of Physics: Conference Series. — 2019. — Vol. 1368. Issue 3.
• 6 Ilyasova N.Yu., Chesnokova T.A. Development of the technique for automatic highlighting ranges of interest in lungs x-ray images // CEUR Workshop Proceedings. — 2019. — Vol. 2391. — P. 128-133
• 7 Surnin O.L., Sitnikov P.V., Khorina A.A. etc. Industrial application of big data services in digital economy // CEUR Workshop Proceedings. — 2019. — Vol. 2416. — P. 409-416
• 8 Shirokanev A.S., Ilyasova N.Yu., Demin N.S. Extracting a DME area based on graph-based image segmentation and collation of OCT retinal images // 2nd International Joint Conference on Computer Vision and Pattern Recognition (CCVPR 2019). — 2019. —
• 9 Ilyasova N., Shirokanev A. S. , Paringer R. etc. Biomedical data analysis based on parallel programming technology application for computation features' effectiveness // 2019 5th International Conference on Frontiers of Signal Processing, ICFSP 2019. — 2019. — P. 67-71

2020

• 1 Shirokanev A. S. , Degtyaryov A., Kibitkina A. S. etc. Development of Information Technology for Selection of Effective Strategy of Diabetic Retinopathy Treatment // Proceedings of the 2020 12th International Conference on Bioinformatics and Biomedical Technology. — 2020. — P. 94-98
• 2 Mukhin A., Kilbas I., Paringer R. etc. Application of the gradient descent for data balancing in diagnostic image analysis problems // Proceedings of ITNT 2020 - 6th IEEE International Conference on Information Technology and Nanotechnology. — 2020. —
• 3 Shirokanev A. S. , Kibitkina A. S. , Ilyasova N.Y. etc. Methods of mathematical modeling of fundus laser exposure for therapeutic effect evaluation // Computer Optics 2020. — Vol. 44. Issue 5. — P. 809-822
• 4 Ilyasova N.Yu., Shirokanev A. S. , Demin N.S. Segmentation of Lung Images Using Textural Features // Journal of Physics: Conference Series. — 2020. — Vol. 1438. Issue 1.
• 5 Shirokanev A. S. , Ilyasova N.Yu., Demin N.S. Analysis of Convolutional Neural Network for Fundus Image Segmentation // Journal of Physics: Conference Series. — 2020. — Vol. 1438. Issue 1.
• 6 Mukhin Artem Vladimirovich, Kilbas I.A., Paringer R.A. etc. Algorithm for Data Balancing Based on Gradient Descent // 2nd International Conference on Advances in Signal Processing and Artificial Intelligence (ASPAI' 2020). — 2020. — P. 56-59
• 7 Ilyasova N., Demin N., Shirokanev A. S. etc. Fundus Image Segmentation Using Decision Trees // Proceedings of ITNT 2020 - 6th IEEE International Conference on Information Technology and Nanotechnology. — 2020. —
• 8 Raku A. V. , Shirokanev A. S. , Degtyarev A. etc. Study of thermal field of the retina of the human eye in the laser exposure zone during numerical simulation based on the solution of the heat equation in the layered region // Proceedings of ITNT 2020 - 6th IEEE International Conference on Information Technology and Nanotechnology. — 2020. —
• 9 Ilyasova N.Y., Shirokanev A. S. , Klimov I. etc. Convolutional Neural Network Application for Analysis of Fundus Images // Advances in Intelligent Systems and Computing. — 2020. — Vol. 1156 AISC. — P. 60-67
• 10 Ilyasova N.Y., Demin N.S., Shirokanev A. S. etc. Method for selection macular edema region using optical coherence tomography data // Computer Optics 2020. — Vol. 44. Issue 2. — P. 250-258
• 11 Mukhin Artem Vladimirovich, Kilbas I.A., Paringer R.A. etc. Применение метода градиентного спуска для балансировки данных в задачах анализа диагностических изображений // Application of the gradient descent for data balancing in diagnostic image analysis problems. — 2020. — Vol. 2. — P. 291-298
• 12 Surnin O.L., Sitnikov P.V., Khorina A.A. etc. Data exchange platform for digital economy // VI Международная конференция и молодёжная школа «Информационные технологии и нанотехнологии» (ИТНТ-2020). — 2020. — Vol. 4. — P. 915-921
• 13 Kilbas Igor Aleksandrovich, R. Paringer, N. Ilyasova etc. Modifying Gradient of a Loss Function to Tackle Class Imbalance // 2nd International Conference on Advances in Signal Processing and Artificial Intelligence (ASPAI' 2020). — 2020. — P. 52-55
• 14 Shirokanev A.S., Kibitkina A.S., Ilyasova N.Yu. etc. Information Technology of Laser Coagulation Strategy Selection in Diabetic Retinopathy Treatment // International Journal of Computational Science and Information Technology (IJCSITY) 2020. — P. 59-64
• 15 Surnin O., Ivaschenko A. V. , Sitnikov P. etc. Data exchange platform for digital economy applications // CEUR Workshop Proceedings. — 2020. — Vol. 2667. — P. 243-247
• 16 Ilyasova N.Y., Shirokanev A. S. , Demin N.S. etc. Information Technology for Decision-making Support for Personalized Parameter Selection in Retinal Laser Treatment and Photocoagulation Outcome Prognostication // Optical Memory and Neural Networks (Information Optics) 2020. — Vol. 29. Issue 4. — P. 358-367

2021

• 1 Ilyasova N., Shirokanev A. S. , Demin N. etc. High-Performance Algorithms Application for Retinal Image Segmentation Based on Texture Features // Lecture Notes in Computer Science. — 2021. — Vol. 12665 LNCS. — P. 198-210
• 2 Ilyasova N., Shirokanev A. S. , Kirsh D. etc. Identification of prognostic factors and predicting the therapeutic effect of laser photocoagulation for dme treatment // Electronics (Switzerland) 2021. — Vol. 10. Issue 12.
• 3 Shirokanev A. S. , Ilyasova N.Y. Intelligent System for Coagulates Preliminary Plan Analysis for Assessment of the Diabetic Retinopathy Treatment Effectiveness // Proceedings of the 2021 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering, ElConRus 2021. — 2021. — P. 1825-1828
• 4 Zamytskiy E.A., Zolotarev A.V., Karlova E.V. etc. Comparative quantitative assessment of the placement and intensity of laser spots for treating diabetic macular edema // Russian Journal of Clinical Ophthalmology 2021. — Vol. 21. Issue 2. — P. 58-62
• 5 Shirokanev A. S. , Ilyasova N., Andriyanov N. etc. Modeling of fundus laser exposure for estimating safe laser coagulation parameters in the treatment of diabetic retinopathy // MATHEMATICS 2021. — Vol. 9. Issue 9.
• 6 Fida A.D., Gaydel A.V., Demin N.S. etc. Automated combination of optical coherence tomography images and fundus images // Computer Optics 2021. — Vol. 45. Issue 5. — P. 721-727
• 7 Mukhin A., Paringer R., Ilyasova N. Feature selection algorithm with feature space separability estimation using discriminant analysis // Proceedings of ITNT 2021 - 7th IEEE International Conference on Information Technology and Nanotechnology. — 2021. —
• 8 Shirokanev A. S. , Ilyasova N.Y., Andriyanov N.A. etc. OCT image processing system for numerical simulation of fundus temperature distribution // Proceedings of SPIE - The International Society for Optical Engineering. — 2021. — Vol. 11793.
• 9 Ilyasova N.Y., Shirokanev A. S. , Demin N.S. Development of High-Performance Algorithms for the Segmentation of Fundus Images Using a Graphics Processing Unit // Pattern Recognition and Image Analysis 2021. — Vol. 31. Issue 3. — P. 529-538
• 10 Shirokanev A. S. , Ilyasova N., Demin N. etc. Extracting a DME area based on graph-based image segmentation and collation of OCT retinal images^∗ // Journal of Physics: Conference Series. — 2021. — Vol. 1780. Issue 1.
• 11 Raku A., Shirokanev A. S. , Degtyarev A. etc. Numerical modeling of the heat conduction equation in a layered region and experimental study of its methodological error // Proceedings of ITNT 2021 - 7th IEEE International Conference on Information Technology and Nanotechnology. — 2021. —
• 12 Surnin O., Stolbova A., Sitnikov P. etc. Digital Transformation of Public Services based on a Content Management System // Proceedings of ITNT 2021 - 7th IEEE International Conference on Information Technology and Nanotechnology. — 2021. —
• 13 Ilyasova N.Y., Demin N.S., Shirokanev A. S. Application of distributed computation of texture features to the analysis of biomedical images // Proceedings of SPIE - The International Society for Optical Engineering. — 2021. — Vol. 11793.
• 14 Shirokanev A. S. , Andriyanov N.A., Ilyasova N.Y. Development of vector algorithm using cuda technology for three-dimensional retinal laser coagulation process modeling // Computer Optics 2021. — Vol. 45. Issue 3. — P. 427-437
• 15 Demin N., Ilyasova N., Golovin A. Retinal Layers Segmentation Technology for Optical Coherence Tomography Images // Proceedings of ITNT 2021 - 7th IEEE International Conference on Information Technology and Nanotechnology. — 2021. —
• 16 Demin N., Ilyasova N., Gaydel A. V. Information technology for estimation accuracy of selection macular edema region in fundus images using OCT data // Proceedings of ITNT 2021 - 7th IEEE International Conference on Information Technology and Nanotechnology. — 2021. —

1995

• 1 Volkova S.E., Ilyasova N.Yu., Ustinov A.V. etc. Methods for analysing the images of blood preparations // Optics and laser technology 1995. — Vol. 27. Issue 4. — P. 255-261
• 2 Brantchevsky S.L., Vasiliev Y.V., Durasov A.B. etc. Method for distinguishing and quantitative evaluation of the elements of pathological pattern of the retina (pathology of microcirculation) // Proceedings of SPIE - The International Society for Optical Engineering. — 1995. — Vol. 2363. — P. 236-242
• 3 Iliasova N.Y., Kichenko S.G., Ustinov A.V. Calculation of compound shape elements (rosette-like) on the blood preparation image // Proceedings of SPIE - The International Society for Optical Engineering. — 1995. — Vol. 2363. — P. 230-235