MUMBAI, India, May 29 -- Intellectual Property India has published a patent application (202641064443 A) filed by Chaitanya Bharathi Institute Of Technology, Kadapa, Andhra Pradesh, on May 21, for 'real-time brain tumor detection using deep learning and vlsi-based medical imaging processor.'
Inventor(s) include J. Raja Kullayappa; G. Jyothindra; K. Praharshini; S. Fayeem Mustafa; B. Sree Latha; V. Manasa; Shaik Shameer; T. Arshad; Dr. Shaik Bajid Vali; N. Mubeen; and R. Mounika.
The application for the patent was published on May 29, under issue no. 22/2026.
According to the abstract released by the Intellectual Property India: "Early and accurate detection of brain tumors from magnetic resonance imaging (MRI) scans is critical for effective diagnosis and treatment planning. However, the increasing volume and resolution of medical imaging data demand intelligent analysis methods along with efficient storage and transmission mechanisms. This paper presents a software-level framework that integrates deep learning-based brain tumor detection with a VLSI-oriented medical image compression processor. A convolutional neural network (CNN) is implemented in MATLAB to automatically classify MRI images into tumor and non-tumor categories after appropriate preprocessing, including resizing and normalization. To enhance storage efficiency, a Verilog-based image compression architecture using Run Length Encoding (RLE) is designed and evaluated using Xilinx Vivado (WebPACK Edition). The compression processor is analyzed through synthesis reports to obtain area, power, and delay metrics, enabling performance evaluation without physical hardware implementation. The proposed approach demonstrates the feasibility of combining artificial intelligence and front-end VLSI design methodologies within a unified, cost-effective software environment for scalable medical imaging applications."
Disclaimer: Curated by HT Syndication.
