MUMBAI, India, Sept. 22 -- Intellectual Property India has published a patent application (202641106026 A) filed by Saveetha Institute Of Medical And Technical Sciences on September 03, 2026, for An Intelligent Diagnostic System For Kidney Tumor Detection Using Machine Learning Technique.
Inventors include Rajagopal K; Dr. V. Sheeja Kumari; Vijayalakshmi R; and Dr Ramya Mohan.
The application for the patent was published on September 18, 2026, under issue no. 38/2026.
Abstract: The present invention relates to an intelligent diagnostic system designed for automated detection and analysis of kidney tumors using machine learning techniques. The system processes medical imaging data obtained from modalities such as computed tomography (CT) scans, magnetic resonance imaging (MRI), and ultrasound imaging to identify abnormal kidney tissue structures. The proposed framework incorporates advanced preprocessing techniques, deep feature extraction methods, and machine learning-based classification algorithms to detect and characterize renal tumors with high accuracy.The invention includes an artificial intelligence-based architecture capable of automatically segmenting tumor regions, extracting clinically relevant features, and classifying tumors into benign or malignant categories. Additionally, the system integrates explainable artificial intelligence (XAI) techniques to provide interpretable diagnostic outputs that assist healthcare professionals in understanding model predictions. The framework further supports cloud-based integration for remote diagnostics and scalable medical data management. A selflearning optimization module enables the model to improve performance over time by continuously updating its parameters using newly available clinical data. The intelligent diagnostic system reduces manual diagnostic workload, improves early detection of kidney cancer, and enhances decision-making support for clinicians. The invention can be deployed in hospitals, diagnostic centers, and telemedicine platforms to enable efficient and accurate kidney tumor detection.
Disclaimer: Curated by HT Syndication.
