MUMBAI, India, Nov. 2 -- Intellectual Property India has published a patent application (202621099557 A) filed by Lnct University; Shalu Arya; and Dr. Vikas Sakalle on August 18, 2026, for A Hybrid Cnn–transformer Deep Learning Framework For Automated Brain Tumor Detection, Classification, And Segmentation Using Mri Images.
Inventors include Shalu Arya; and Dr. Vikas Sakalle.
The application for the patent was published on October 30, 2026, under issue no. 44/2026.
Abstract: A Transformer-Enhanced Deep Learning Framework for Automated Brain Tumor Detection, Classification, Segmentation and Localization. The present invention relates to a Transformer-enhanced deep learning-based system and method for automated brain tumor detection, classification, segmentation, and localization using magnetic resonance imaging (MRI) data. The invention addresses limitations of conventional medical image analysis approaches by providing an automated and intelligent framework capable of identifying and characterizing brain tumors from MRI images. By integrating convolutional neural networks (CNNs) with Transformer-based attention mechanisms, the system captures both local spatial features and global contextual relationships, thereby supporting accurate and comprehensive brain tumor analysis.
Disclaimer: Curated by HT Syndication.
