RADIOLOGIK DIAGNOSTIKA TASVIRLARINI TAHLIL QILUVCHI VEYVLETLARGA ASOSLANGAN KONVOLUTSION NEYRON TARMOQ ARXITEKTURASI

Umidjon Jurayev

Авторы

Umidjon Jurayev Guliston davlat universiteti

Ключевые слова:

Veyvlet, diskret o‘zgartirish, Dobeshi veyvleti, CNN, WCNN, KQR tasvirlari, neyron tarmoq

Аннотация

Maqolada eng keng tarqalgan o‘pka kasalliklarini aniqlash uchun ko‘p sinfli chuqur o‘rganishli tasniflash modeli taqdim etiladi. Tadqiqotimizning asosiy masalasi chuqur o‘rganish tizimini ishlab chiqish va ko‘p toifali pnevmoniya, sil, sog‘lom o‘pka va eng so‘nggi COVID-19 ni tasniflashdan iborat. Chuqur o‘rganish sohasidagi tadqiqotlar raqamli tasvirlarda o‘pka kasalliklarini tasniflash va tashxislash muammolariga muhim yechimlarni taqdim etishda davom etmoqda. Shuning uchun, biz bu tadqiqotda ushbu muammolarni ikkinchi tartibli Dobeshi veyvletini qo‘llagan holda veyvlet-CNN arxitekturasi orqali hal qilishga harakat qildik.

Библиографические ссылки

Воробьев В.И., Грибунов В.Г. Теория и практика вейвлет-преобразования. – ВУС, 1999. – 206 с.

Дремин И.М., Иванов О.В., Нечитайло В.А. Вейвлеты и их использование. – УФН, 171:5 (2001). – C. 465-501.

Жураев У.С. Добеши вейвлетлари ёрдамида тасвирларга рақамли ишлов бериш // “Фан, таълим ва техникани инновацион ривожлантириш масалалари”. Халқаро илмий-амалий онлайн анжуман материаллари тўплами. – Андижон, 2022. – Б. 71-74.

Симонов К.В., Хамад Ю.А., Кенц А.С. Нейросетевые алгоритмы классификации патологии легких на рентгеновских снимках //Нейроинформатика, ее приложения и анализ данных: Материалы XXVI Всероссийского семинара. – Красноярск: ИВМ СО РАН, 2019. – С. 104-109.

Хамад Ю.А. и др. Вычислительная методика обработки медицинских изображений, используя вейвлет и нейросети // Медицина и высокие технологии. 2018. №. 3. – С. 5-13.

Albahli S., Efficient gan-based chest radiographs (CXR) augmentation to diagnose coronavirus disease pneumonia, Int. J. Med. Sci. 17 (10) (2020) – p. 1439–1448, https://doi.org/10.7150/ IJMS.46684.

Chandra T.B., K.Verma, B.K.Singh, D. Jain, S.S.Netam, Automatic detection of tuberculosis related abnormalities in Chest X-ray images using hierarchical feature extraction scheme, Expert Syst. Appl. 158 (2020), https://doi.org/10.1016/j. eswa.2020.113514.

Daubechies I., Ten lectures on wavelets.CBMS-NSF Regional Conf. Ser. in Appl. Math., 61 Society for Industrial and Applied Mathematics (SIAM), Philadelphia, PA, 1992. xx+357 pp. ISBN:0-89871-274-2.

Jurayev U.S. A convolutional neural network model based on wavelets for cancer type classification in lung tomographic images // Bulletin of TUIT: Management and Communication Technologies Vol. 2, No. 7, 2023. (05.00.00; 30.07.2020-yildagi O‘zR Vazirlar Mahkamasi huzuridagi OAK Rayosatining № 283/7.1 qarori)

Jurayev U.S. Tasvirlarga raqamli ishlov berishda Dobeshi veyvlet modellaridan foydalanish // “Raqamli texnologiyalar va sun’iy intellektni rivojlantirishning zamonaviy holati va istiqbollari” mavzusidagi Respublika ilmiy-amaliy anjumani materiallari to‘plami. – Guliston, 22-23-dekabr, 2022. –B. 86-90

Kumar J.S., S.A. Alias Balamurugan, S. Sasikala, Analysis of Deep Learning Techniques for Tuberculosis Disease, SN Comput. Sci. 2 (4) (2021) -P. 1–10, https://doi.org/10.1007/s42979- 021-00680-y.

Rahimzadeh M., A. Attar, A modified deep convolutional neural network for detecting COVID-19 and pneumonia from chest X-ray images based on the concatenation of Xception and ResNet50V2, Inform. Med. Unlocked 19 (2020), https://doi.org/ 10.1016/j.imu.2020.100360 100360.

Sathitratanacheewin S., P. Sunanta, K. Pongpirul, Deep learning for automated classification of tuberculosis-related chest X-Ray: dataset distribution shift limits diagnostic performance generalizability, Heliyon 6 (8) (2020) e04614.

Thamilarasi V., Roselin R. Automatic classification and accuracy by deep learning using CNN methods in lung chest x-ray images. IOP Conf. Ser. Mater. Sci. Eng. 2021;1055:012099. doi: 10.1088/1757-899X/1055/1/012099. [CrossRef] [Google Scholar]

Zaynidinov H.N., Jurayev U.S., Tishlikov S.A., J.Modullayev Application of Daubechies Wavelets in Digital Processing of Biomedical Signals and Images, IHCI 2023: Intelligent Human Computer Interaction. Pp- 194–206, https://doi.org/10.1007/978-3-031-53827-8_19.