Поиск :
Личный кабинет :
Электронный каталог: Deeva, O. - An Algorithm on the Preprocessing Optical Microscopy Image
Deeva, O. - An Algorithm on the Preprocessing Optical Microscopy Image
Книга (аналит. описание)
Автор: Deeva, O.
Информационно-телекоммуникационные технологии и математическое моделирование высокотехнологичных систем: An Algorithm on the Preprocessing Optical Microscopy Image
б.г.
ISBN отсутствует
Автор: Deeva, O.
Информационно-телекоммуникационные технологии и математическое моделирование высокотехнологичных систем: An Algorithm on the Preprocessing Optical Microscopy Image
б.г.
ISBN отсутствует
На полку
Книга (аналит. описание)
Deeva, O.
An Algorithm on the Preprocessing Optical Microscopy Image / O.Deeva, M.Cosic, I.Kolesnikova, S.Z.Despotovic // Информационно-телекоммуникационные технологии и математическое моделирование высокотехнологичных систем : материалы Всероссийской конференции с международным участием, Москва, РУДН, 8-12 апреля 2024 г. [Электронный ресурс]. – М. : РУДН, 2024. – C. 443-449. – URL: http://inis.jinr.ru/sl/NTBLIB/ITTMMH-2024-P443.pdf. – Bibliogr.: 9.
The task of recognizing and classifying neurons is now relevant for histological image analysis. Nowadays, the cells are being counted manually, so image processing is error-prone and takes a lot of time. That is why it is important to create a tool to help classify cells according to some mathematical properties that faithfully reflect their histological classification. In our case, the classification was done according to the multiscale structural complexity. The first step in creating such a tool is developing a special method of preprocessing optical microscopy images. Experimental images possess two features that corrupt complexity calculations: a significant variation of the light intensity from the bright center to the dark edges of the image and a lack of clarity of small objects. An algorithm has been developed to solve both of these problems, which, in essence, reduces to the determination of the average light intensity and its subtraction from the initial image. This method enhances the visibility of smaller objects in the image, by making their edges sharper. Also, thanks to subtraction, the dark edges of the image, obtained due to the microscope, were lightened, which improves the visibility of cells located far from the center of the image. Both improvements enhance the distinguishability of the complexity distributions corresponding to different histological types, then those built using raw data. The developed algorithm should be useful, in general, for the preprocessing of histological microscopy images.
Спец.(статьи,препринты) = С 37 - Оптика$
Спец.(статьи,препринты) = С 17 к - Расчеты по молекулярной динамике. Численное моделирование физических задач
Спец.(статьи,препринты) = 28.0 - Биология$
ОИЯИ = ОИЯИ (JINR)2024
Deeva, O.
An Algorithm on the Preprocessing Optical Microscopy Image / O.Deeva, M.Cosic, I.Kolesnikova, S.Z.Despotovic // Информационно-телекоммуникационные технологии и математическое моделирование высокотехнологичных систем : материалы Всероссийской конференции с международным участием, Москва, РУДН, 8-12 апреля 2024 г. [Электронный ресурс]. – М. : РУДН, 2024. – C. 443-449. – URL: http://inis.jinr.ru/sl/NTBLIB/ITTMMH-2024-P443.pdf. – Bibliogr.: 9.
The task of recognizing and classifying neurons is now relevant for histological image analysis. Nowadays, the cells are being counted manually, so image processing is error-prone and takes a lot of time. That is why it is important to create a tool to help classify cells according to some mathematical properties that faithfully reflect their histological classification. In our case, the classification was done according to the multiscale structural complexity. The first step in creating such a tool is developing a special method of preprocessing optical microscopy images. Experimental images possess two features that corrupt complexity calculations: a significant variation of the light intensity from the bright center to the dark edges of the image and a lack of clarity of small objects. An algorithm has been developed to solve both of these problems, which, in essence, reduces to the determination of the average light intensity and its subtraction from the initial image. This method enhances the visibility of smaller objects in the image, by making their edges sharper. Also, thanks to subtraction, the dark edges of the image, obtained due to the microscope, were lightened, which improves the visibility of cells located far from the center of the image. Both improvements enhance the distinguishability of the complexity distributions corresponding to different histological types, then those built using raw data. The developed algorithm should be useful, in general, for the preprocessing of histological microscopy images.
Спец.(статьи,препринты) = С 37 - Оптика$
Спец.(статьи,препринты) = С 17 к - Расчеты по молекулярной динамике. Численное моделирование физических задач
Спец.(статьи,препринты) = 28.0 - Биология$
ОИЯИ = ОИЯИ (JINR)2024
