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Deep Learning-Based Renal Stone Detection: A Comprehensive Study and Performance Analysis Cover

Deep Learning-Based Renal Stone Detection: A Comprehensive Study and Performance Analysis

Applied Computer Systems
Volume 29 (2024): Issue 1 (June 2024)
By: Priyadharsini Ravisankar,  Varsha Balaji and  Shahul Hameed T  
Open Access
|Aug 2024

Authors

Priyadharsini Ravisankar

priyadharsinir@ssn.edu.in

Department of Computer Science and Engineering, Sri Sivasubramaniya Nadar College of Engineering, Chennai, India

Varsha Balaji

varsha2010399@ssn.edu.in

Department of Computer Science and Engineering, Sri Sivasubramaniya Nadar College of Engineering, Chennai, India

Shahul Hameed T

shahul2012066@ssn.edu.in

Department of Computer Science and Engineering, Sri Sivasubramaniya Nadar College of Engineering, Chennai, India
DOI: https://doi.org/10.2478/acss-2024-0014 | Journal eISSN: 2255-8691 | Journal ISSN: 2255-8683
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Language: English
Page range: 112 - 116
Submitted on: Feb 6, 2024
Accepted on: Jul 29, 2024
Published on: Aug 15, 2024
Published by: Riga Technical University
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year
Keywords:
CT images,
deep learning models,
detection,
renal stone
Related subjects:
Computer sciences,
Artificial intelligence,
Information technology,
Project management,
Software development

© 2024 Priyadharsini Ravisankar, Varsha Balaji, Shahul Hameed T, published by Riga Technical University
This work is licensed under the Creative Commons Attribution 4.0 License.

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