12
hududlarni muvaffaqiyatli aniqlaydi. Tibbiy tasvir namunasini tahlil qilishning ish
jarayoni 1-rasmda ko‘rsatilgan.
1-rasm: Tibbiy tasvir namunasi tahlili tuzilishi
1-rasmda tasvirni oldindan qayta ishlash va segmentatsiya bosqichlaridan iborat
tibbiy tasvir namunasini tahlil qilish strukturasi tasvirlangan
Xulosa
O’rganilgan tadqiqotlar natijasida chiqarilgan hududning samaradorligi tibbiy
tasvirning deyarli barcha xususiyatlarini qamrab oluvchi taqsimot shaklini moslashtirish
qoidasi yordamida aniqlanadi va umumiy tibbiy tasvir
namunasini tahlil qilish
jarayonini yaxshilashga yordam beradi. Bu jarayon hisoblash murakkabligini
minimallashtiradi va kasallikdan ta'sirlangan hududlarning aniqligini 99%
gacha
chiqarilishi ma`lum bo’ldi.
Adabiyotlar ro‘yxati:
1.
Sadullaeva Sh.A., Aripova Z.D, Rajabova M.R
., “Ayollarda Uchraydigan
Mioma Kasalligini Segmentatsiyalash Orqali Aniqlash” “Zamonaviy Axborot,
Kommunikatsiya Texnologiyalari Va At-Ta’lim Tatbiqi Muammolari” Mavzusidagi
Respublika
Ilmiy-Amaliy Anjumani, Samarqand, pp. 88–90, 2022.
2.
S. Anwar, M. Majid, A. Qayyum, M. Awais, M. Alnowami et al., “Medical
image analysis using convolutional neural networks: A review,”
Journal of Medical
Systems, vol. 42, no. 11, pp. 226, 2018.
3.
H. Chen, X.Qi, L.Yu, Q. Dou, J.Qin, and P.-A. Heng, "DCAN: Deep
contour-aware networks for object instance segmentation from histology images,"
Medical Image
Analysis, vol. 36, pp. 135-146, 2017/02/01/, 2017.
13
4.
H.-C. Shin, H. R. Roth, M. Gao, L. Lu, Z. Xu, I. Nogues, et al., "Deep
convolutional neural networks for computer-aided detection: CNN architectures, dataset
characteristics and transfer learning," vol. 35, pp. 1285-1298, 2016.
5.
N. Tajbakhsh, J. Y. Shin, S. R. Gurudu, R. T. Hurst, C. B. Kendall, M. B.
Gotway, et al., "Convolutional Neural Networks for Medical Image Analysis: Full
Training or Fine Tuning?," IEEE Transactions on Medical Imaging, vol. 35, pp. 1299-
1312, 2016.
6.
M. Abdel-Basset, G. Manogaran, D. El-Shahat and S. Mirjalili, “A hybrid
whale optimization algorithm based on local search strategy for the permutation flow
shop scheduling problem,” Future Generation Computer Systems, vol. 85, pp. 129–145,
2018.
