ADAPTIV GISTOGRAMMA TEKISLASH (AHE) ASOSIDA TIBBIY TASVIRLARNI SEGMENTATSIYALASH
Ключевые слова:
Tibbiy tasvirlar, topografik xarita, AHE algoritmi, tasvir sifatini yaxshilash.Аннотация
Yurak kasalliklarini erta aniqlashda yurak tasvirlari — xususan, echokardiyografiya, MRT va KT tasvirlari muhim manba hisoblanadi. Biroq, past kontrastli yoki shovqinli tasvirlar diagnostik jarayonni murakkablashtiradi. Ushbu maqolada tasvir sifatini yaxshilash uchun Adaptive Histogram Equalization (AHE) algoritmidan foydalaniladi. AHE yordamida yaxshilangan yurak tasviri ustida chekka aniqlovchi va topografik xarita asosidagi segmentatsiya amallari bajariladi. Ushbu yondashuv yurakning klapanlari, devorlari va bo‘lmachalarining konturlarini aniqroq aniqlashga imkon beradi.
Библиографические ссылки
Pizer, S. M., et al. (1987). Adaptive Histogram Equalization and Its Variations. CVGIP.
Zuiderveld, K. (1994). Contrast Limited Adaptive Histogram Equalization. Graphics Gems IV.
Kaur, A. & Kaur, P. (2018). Comparison of AHE and Gamma Correction for Medical Imaging.
Sundararajan, K., et al. (2016). Medical Image Segmentation with Preprocessed Deep Learning.
Sharma, A., et al. (2020). Topographic Map-Based Tumor Segmentation. IEEE Transactions.
S. K. Fazilov, O. R. Yusupov and K. S. Abdiyeva, "An Algorithm for Evaluating the Parameters Characterizing the Quality of the Image Field of the Iris by the Principal component analysis method," 2022 International Conference on Information Science and Communications Technologies (ICISCT), Tashkent, Uzbekistan, 2022, pp. 1-4, doi: 10.1109/ICISCT55600.2022.10146887.
Suganya, R.; Rajaram, S.; Abdullah, A.S. Big Data in Medical Image Processing; Taylor & Francis: Oxford, UK, 2018.
Singh, H. Practical Machine Learning and Image Processing; Springer Science & Business Media: New York, NY, USA, 2019.
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