Intellectual Property India Publishes Patent Application for 'An Efficient Convolutional Neural Network-based System For Binary Classification Of Brain Tumors From Medical Images' Filed by Lnct University

MUMBAI, India, Feb. 27 -- Intellectual Property India has published a patent application (202621005725 A) filed by Lnct University, Bhopal, Madhya Pradesh, on Jan. 20, for 'an efficient convolutional neural network-based system for binary classification of brain tumors from medical images.'

Inventor(s) include Neha Rai; and Dr. Vikas Sakalle.

The application for the patent was published on Feb. 27, under issue no. 09/2026.

According to the abstract released by the Intellectual Property India: "An efficient convolutional neural network-based system and method for binary classification of brain tumors from medical images is disclosed. The invention provides an automated diagnostic framework that acquires brain medical images, preprocesses the images to enhance diagnostic quality, and analyzes the images using an optimized convolutional neural network to determine presence or absence of brain tumors. The system eliminates reliance on handcrafted features and manual interpretation by learning hierarchical representations directly from medical images. The invention achieves high classification accuracy with reduced computational complexity and supports real-time clinical workflows. The disclosed system is suitable for deployment in hospitals, diagnostic centers, and telemedicine platforms, particularly in resource-constrained environments, thereby improving early detection, diagnostic consistency, and healthcare accessibility."

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