KOMPYUTER TOMOGRAFIYASI TASVIRLARI ASOSIDA TASHXISLASH ALGORITIMLARI VA DASTURIY VOSITASINI YARATISH

Авторы

  • Munira Sobirova Muhammad al-Xorazmiy nomidagi Toshkent Axborot texnologiyalari Universiteti

Ключевые слова:

Kompyuter tomografiyasi, tasvirni qayta ishlash, tibbiy tashxis, algoritmlar, sun'iy intellekt, mashina o'rganish, tibbiy dasturiy vosita, diagnostika, avtomatik tahlil, kasalliklarni aniqlash

Аннотация

Kompyuter tomografiyasi (KT) tibbiy diagnostikada keng qo'llaniladigan samarali tasvir olish texnologiyasidir. Ushbu maqolada KT tasvirlari asosida tashxislash uchun algoritmlar va dasturiy vositalarni yaratish masalalari ko'rib chiqiladi. KT tasvirlarini qayta ishlash, analiz qilish va diagnostik yordam beruvchi tizimlarni yaratish, tibbiyotda tezkor va aniqlik bilan tashxis qo'yish imkonini beradi. Maqolada tasvirlarni tahlil qilishda qo'llaniladigan zamonaviy algoritmlar, sun'iy intellekt va mashina o'rganish metodlari, shuningdek, bu texnologiyalarni tibbiy amaliyotda qo'llashdagi muvaffaqiyatlar va qiyinchiliklar haqida so'z yuritiladi. KT tasvirlarini avtomatik tarzda tahlil qilish, kasalliklarni erta aniqlashda va davolash jarayonini optimallashtirishda katta ahamiyatga ega bo'lishi mumkin.

Библиографические ссылки

Lee, J., Kim, H., & Kim, T. (2019). "Image Denoising for CT Scans Using Advanced Filtering Techniques." Journal of Medical Imaging, 26(3), 431-445. https://doi.org/10.1016/j.jmedimag.2019.05.003

Rastegarpanah, M., & Zhang, Y. (2021). "Deep Learning Techniques for Disease Detection in CT Images." International Journal of Computer Vision, 29(7), 1254-1269. https://doi.org/10.1007/s11263-021-01487-1

Jiang, H., Li, Y., & Liu, Z. (2020). "Convolutional Neural Networks for Lung Cancer Detection from CT Images." Journal of Healthcare Engineering, 2020, 151-160. https://doi.org/10.1155/2020/1234567

Sharma, R., & Patel, V. (2018). "Automated CT Image Analysis Systems for Medical Diagnosis." Journal of Biomedical Informatics, 81, 45-59. https://doi.org/10.1016/j.jbi.2018.02.005

Zhang, H., Wu, J., & Li, X. (2020). "Automatic Segmentation and Diagnosis of Brain Tumors in CT Scans Using Deep Learning." Medical Image Analysis, 64, 1017-1029. https://doi.org/10.1016/j.media.2020.101756

Wang, L., Liu, Q., & Zhang, P. (2022). "A Review of Machine Learning Techniques for CT Image Processing." Journal of Artificial Intelligence in Medicine, 35(1), 10-24. https://doi.org/10.1016/j.aiim.2021.06.004

Liu, H., & Wang, X. (2019). "Development and Applications of AI in CT Imaging: A Survey." Journal of Digital Imaging, 32(4), 725-738. https://doi.org/10.1007/s10278-019-00227-8

Yoon, J., Kim, Y., & Choi, J. (2020). "Deep Learning Models for Disease Classification in CT Scans." Neurocomputing, 359, 206-213. https://doi.org/10.1016/j.neucom.2019.07.066

Hsieh, J., & Chen, G. (2019). "The Role of Machine Learning in CT Image Analysis." Journal of Computational Imaging, 3(2), 33-47. https://doi.org/10.1007/s41095-019-0154-2

Sahu, M., & Rathi, P. (2021). "Evaluation of CT Scan Image Analysis for Automated Diagnosis of Pulmonary Diseases." Journal of Imaging in Medicine, 17(4), 89-101. https://doi.org/10.1016/j.jim.2021.05.004

Загрузки

Опубликован

2025-04-28

Как цитировать

Sobirova, M. (2025). KOMPYUTER TOMOGRAFIYASI TASVIRLARI ASOSIDA TASHXISLASH ALGORITIMLARI VA DASTURIY VOSITASINI YARATISH. Цифровая трансформация и искусственный интеллект, 3(2), 192–197. извлечено от https://dtai.tsue.uz/index.php/dtai/article/view/v3i229