NOVEL APPROACH FOR KIDNEY STONE DETECTION THROUGH ULTRASOUND IMAGES USING AGGREGATION FILTER MECHANISMS
Title: Novel Approach for Kidney Stone Detection Through Ultrasound Images Using Aggregation Filter Mechanisms
Permalink: http://www.ijetjournal.org/kidney-stone-detection-ultrasound
Description: This paper explores an automated kidney stone classification system using image processing and deep learning. It examines MRI and CT scan images, leveraging neural networks to enhance detection accuracy for nephrolithiasis.
Keywords: Kidney stone detection, Deep learning-based approaches, CNN classification, Feature extraction, IJET Journal
International Journal of Engineering and Techniques – Volume 10 Issue 2, April 2024
Dr. D J Samatha Naidu, B. Yamini
Annamacharya PG College of Computer Studies, Rajampet, India
Email: samramana44@gmail.com, yaminiprasad1971@gmail.com
Abstract
Kidney stone detection has seen significant advancements with deep learning methodologies. This paper investigates an automated classification system using MRI and CT scan preprocessing. It leverages neural networks for feature extraction, highlighting their effectiveness in nephrolithiasis detection. The study emphasizes the role of image processing in refining detection accuracy and optimizing healthcare diagnostics.
Keywords
Kidney stone detection, Deep learning-based approaches, CNN classification, Feature extraction, Transfer learning
How to Cite
Dr. D J Samatha Naidu, B. Yamini, “Novel Approach for Kidney Stone Detection Through Ultrasound Images Using Aggregation Filter Mechanisms,” International Journal of Engineering and Techniques, Volume 10, Issue 2, April 2024. ISSN 2395-1303
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