Kidney Stone Detection Using Resnet Algorithm

The Kidney Condition Detection System (KCDS) uses MRI images and advanced image processingtechniques to improve the early and accurate diagnosis of kidney diseases. By leveraging a ResNet-basedneural network, the system automatically extracts relevant features from MRI images, allowing for acomprehensive analysis of kidney structure and function. This approach enables the detection of subtlechanges in renal anatomy that could indicate early-stage conditions like chronic kidney disease or renaltumors. KCDS's integration of a diverse MRI image database enhances its adaptability and accuracyacross different patient demographics and disease presentations. The system aims to revolutionize kidneydisease diagnosis by providing detailed, automated, and precise assessments that surpass traditionalmethods

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-08-11
DOI
https://doi.org/10.5281/zenodo.16795121
Primary Topic
Renal cell carcinoma treatment
Type
article
Field-Weighted Citation Impact
0.00
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article

Kidney Stone Detection Using Resnet Algorithm

Zenodo (CERN European Organization for Nuclear Research)
Renal cell carcinoma treatment
article

Kidney Stone Detection Using Resnet Algorithm

article en

Abstract

The Kidney Condition Detection System (KCDS) uses MRI images and advanced image processingtechniques to improve the early and accurate diagnosis of kidney diseases. By leveraging a ResNet-basedneural network, the system automatically extracts relevant features from MRI images, allowing for acomprehensive analysis of kidney structure and function. This approach enables the detection of subtlechanges in renal anatomy that could indicate early-stage conditions like chronic kidney disease or renaltumors. KCDS's integration of a diverse MRI image database enhances its adaptability and accuracyacross different patient demographics and disease presentations. The system aims to revolutionize kidneydisease diagnosis by providing detailed, automated, and precise assessments that surpass traditionalmethods

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 38%
Renal cell carcinoma treatment
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