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In this article, we introduce an automated method for delineating kidneys in computed tomography (CT) images using a combination of advanced image processing techniques, including Convolutional Neural Networks (CNNs) and the Watershed segmentation algorithm. After detecting kidney stones, patients can input crucial health parameters-such as kidney size, shape, injuries, and infections-through an intuitive user interface. Based on these inputs and the diagnosed kidney stones, a personalized diet plan is generated. This holistic approach not only improves diagnostic accuracy but also enhances patient involvement and provides customized dietary recommendations, effectively aiding in the prevention of kidney stones.
Ahmad et al. (Mon,) studied this question.