SmartUro: An Advanced Deep Learning Framework for Automated Kidney Stone Detection and Classification in Medical Imaging

• Author(s): Swaroop M; Nandan Gowda H M; Rakshitha P; Praveen Kamalappanavar; Satisha T
• Paper ID: 1712231
• Page: 2214-2219
• Published Date: 28-11-2025
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 9 Issue 5 November-2025
• DOI: https://doi.org/10.64388/IREV9I5-1712231

Abstract

Kidney stone disease affects 10-15% of the global population, yet traditional diagnostic methods are time-intensive and error-prone. This paper presents SmartUro, an intelligent diagnostic system leveraging YOLOv8 deep learning architecture for automated kidney stone detection across CT, MRI, X-ray, and ultrasound imaging. Our system achieves 93.0% mean Average Precision (mAP50), with 93.8% precision and 92.9% recall, processing images in under 3 seconds. Through multi-dataset integration and systematic optimization, SmartUro demonstrates clinical-grade accuracy suitable for deployment in both well-resourced centers and underserved facilities. A Streamlit-based web interface enables real-time clinical integration with comprehensive diagnostic reporting.

Keywords

Kidney Stone Detection, YOLOv8, Deep Learning, Medical Image Analysis, Automated Diagnosis

Citations

IRE Journals:
Swaroop M, Nandan Gowda H M, Rakshitha P, Praveen Kamalappanavar, Satisha T "SmartUro: An Advanced Deep Learning Framework for Automated Kidney Stone Detection and Classification in Medical Imaging" Iconic Research And Engineering Journals Volume 9 Issue 5 2025 Page 2214-2219 https://doi.org/10.64388/IREV9I5-1712231

IEEE:
Swaroop M, Nandan Gowda H M, Rakshitha P, Praveen Kamalappanavar, Satisha T "SmartUro: An Advanced Deep Learning Framework for Automated Kidney Stone Detection and Classification in Medical Imaging" Iconic Research And Engineering Journals, vol. 9, no. 5, Nov. 2025, doi: https://doi.org/10.64388/IREV9I5-1712231

APA:
Swaroop M, Nandan Gowda H M, Rakshitha P, Praveen Kamalappanavar, Satisha T (2025). SmartUro: An Advanced Deep Learning Framework for Automated Kidney Stone Detection and Classification in Medical Imaging. Iconic Research And Engineering Journals, 9(5). doi: https://doi.org/10.64388/IREV9I5-1712231

MLA:
Swaroop M, Nandan Gowda H M, Rakshitha P, Praveen Kamalappanavar, Satisha T "SmartUro: An Advanced Deep Learning Framework for Automated Kidney Stone Detection and Classification in Medical Imaging" Iconic Research And Engineering Journals, vol. 9, no. 5, Nov. 2025. Crossref, https://doi.org/10.64388/IREV9I5-1712231

BibTeX

@article{1712231,
author = {Swaroop M, Nandan Gowda H M, Rakshitha P, Praveen Kamalappanavar, Satisha T},
title = {SmartUro: An Advanced Deep Learning Framework for Automated Kidney Stone Detection and Classification in Medical Imaging},
journal = {Iconic Research And Engineering Journals},
year = {2025},
volume = {9},
number = {5},
pages = {2214-2219},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1712231.pdf},
abstract = {Kidney stone disease affects 10-15% of the global population, yet traditional diagnostic methods are time-intensive and error-prone. This paper presents SmartUro, an intelligent diagnostic system leveraging YOLOv8 deep learning architecture for automated kidney stone detection across CT, MRI, X-ray, and ultrasound imaging. Our system achieves 93.0% mean Average Precision (mAP50), with 93.8% precision and 92.9% recall, processing images in under 3 seconds. Through multi-dataset integration and systematic optimization, SmartUro demonstrates clinical-grade accuracy suitable for deployment in both well-resourced centers and underserved facilities. A Streamlit-based web interface enables real-time clinical integration with comprehensive diagnostic reporting.},
keywords = {Kidney Stone Detection, YOLOv8, Deep Learning, Medical Image Analysis, Automated Diagnosis},
month = {November}
}