TIBBIY TASVIRLARNI TAHLIL QILISH USUL VA ALGORITMLARI

Mamatov N.S; Jo‘rayev I.A; Jalelova M.M; Jumayev B.J

TIBBIY TASVIRLARNI TAHLIL QILISH USUL VA ALGORITMLARI

Authors

Mamatov N.S “Toshkent irrigatsiya va qishloq xo‘jaligini mexanizatsiyalash muhandislari instituti” Milliy tadqiqot universiteti
Jo‘rayev I.A “Toshkent irrigatsiya va qishloq xo‘jaligini mexanizatsiyalash muhandislari instituti” Milliy tadqiqot universiteti
Jalelova M.M “Toshkent irrigatsiya va qishloq xo‘jaligini mexanizatsiyalash muhandislari instituti” Milliy tadqiqot universiteti
Jumayev B.J “Toshkent irrigatsiya va qishloq xo‘jaligini mexanizatsiyalash muhandislari instituti” Milliy tadqiqot universiteti

Keywords:

Segmentatsiya algoritmlari, tasniflash, chuqur o‘qitish, convolutional Neural Networks (CNN), U-Net, thresholding, Watershed algoritmi.

Abstract

This work analyzes modern approaches to medical image analysis for early
detection of kidney diseases, and studies the role of segmentation and classification algorithms in
detecting kidney tumors, stones, and other pathological conditions based on CT, MRI, and
ultrasound images. In particular, it is emphasized that deep learning models such as CNN and UNet
have high accuracy. At the end of the study, a comparative analysis of the algorithms is
presented.

References

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TIBBIY TASVIRLARNI TAHLIL QILISH USUL VA ALGORITMLARI