Phát hiện sỏi thận sử dụng ision transformer

Abstract

Kidney stones are the primary cause of illness, and the incidence of this condition is increasing worldwide. Delayed kidney stone diagnosis can lead to complications such as urinary tract infections, kidney obstruction, and irreversible kidney damage, potentially resulting in significant economic and even life-threatening consequences if not treated promptly. Therefore, early detection and treatment of kidney stones are essential. Furthermore, Vision Transformer (ViT) has emerged as a competitive alternative to traditional convolutional neural networks in the field of computer vision and is widely used in various image recognition tasks. In this paper, we propose a method for kidney stone detection using Vision Transformer. Research results demonstrate that the proposed method achieves an accuracy rate of up to 93% on CT image datasets during the training process.