Intellectual Property India Publishes Patent Application for 'An AI-Driven Web-Based System For Brain Tumor Detection And Classification From Mri Images' Filed by Vel Tech Multi Tech Dr. Rangarajan Dr. Sakunthala Engineering College; Dr. Palanikumar S; Rajavignesh M U; Akash S; Sarvesh R; and Roshakpradeepan D

MUMBAI, India, March 13 -- Intellectual Property India has published a patent application (202641005019 A) filed by Vel Tech Multi Tech Dr. Rangarajan Dr. Sakunthala Engineering College; Dr. Palanikumar S; Rajavignesh M U; Akash S; Sarvesh R; and Roshakpradeepan D, Chennai, Tamil Nadu, on Jan. 19, for 'an ai-driven web-based system for brain tumor detection and classification from mri images.'

Inventor(s) include Dr. Palanikumar S; Rajavignesh M U; Akash S; Sarvesh R; and Roshakpradeepan D.

The application for the patent was published on March 13, under issue no. 11/2026.

According to the abstract released by the Intellectual Property India: "An AI-Driven Web-Based System for Brain Tumor Detection and Classification from MRI Images ADSTRACT OF THE INVENTION The proposed system is a web-bas~d brain tumor detection and classification platform that enables users to upload . . . . . . . . . . and analyze MRI images directly through a standard web browser without requiring server-side computation. The system includes an image preprocessing module that performs resizing, normalization, and format conversion to prepare MRT images for analysis. A browser-executable artificial intelligence model then detects the presence of . . . brain tumors and classifies them into categories such as glioma, meningioma, or pituitary tumor. All processing is performed locally on the user's device, ensuring real-time performance, data privacy, and accessibility across multiple computing platforms. The system further includes a result visualization module that highlights tumor regions and displays classification outcomes through an interactive interface. By eliminating dependency on backend servers or cloud infrastructure, the invention reduces latency, preserves sensitive medical data, and . . . ' . . . . . . supports ppe~ation .in IQw-r:e_sou.rce envjronments .. The modular design allows future enhancements, including additional tumor classifications and advanced visualization features. Overall, the invention provides a secure, scalable, and "accessible solution for imtomated brain tumor analysis."

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