Utilizing Deep Learning to Detect Kidney Stones from CT Scan Data

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.

Authors

Publication Details

Journal
International Journal of Science and Research (IJSR)
Published
2024-08-05
DOI
https://doi.org/10.21275/sr24804133936
Primary Topic
Advanced X-ray and CT Imaging
Type
article
Field-Weighted Citation Impact
0.00
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article

Utilizing Deep Learning to Detect Kidney Stones from CT Scan Data

Naseem Ahmad, Arif Ali
International Journal of Science and Research (IJSR)
Advanced X-ray and CT Imaging
article

Utilizing Deep Learning to Detect Kidney Stones from CT Scan Data

Naseem Ahmad, Arif Ali
article en

Abstract

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.

International Journal of Science and Research (IJSR)Vol. 13(8)
Openalex Percentile: Top 89%
Advanced X-ray and CT Imaging
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