MUMBAI, India, June 22 -- Intellectual Property India has published a patent application (202641050145 A) filed by Hindusthan College Of Engineering And Technology on April 20, 2026, for Optimized Brain Stroke Detection Using Python Based Image Processing.
Inventor includes Hindusthan College Of Engineering And Technology.
The application for the patent was published on June 12, 2026, under issue no. 24/2026.
Abstract: OPTIMIZED BRAIN STROKE DETECTION USING PYTHON BASED IMAGE PROCESSING ABSTRACT Magnetic Resonance Imaging (MRI) plays a crucial role in the detection and monitoring of brain strokes, where accurate and timely diagnosis is essential for effective treatment. However, manual identification and segmentation of stroke-affectec;l regions are time-consuming, prone to human error, and often inconsistent across clinicians. Existing automated approaches either rely heavily on handcrafted features or require large volumes of annotated data, which are difficult to obtain due to privacy and data scarcity ISSUeS. To address these challenges, this project proposes an optimized brain stroke detection system using a Python-based image processing framework combined with deep learning techniques. The proposed method employs a two-pathway Convolutional Neural Network (CNN) architecture capable of capturing both fine local details and global contextual information from MRl scans. This dual-pathway design enhances the model's ability to detect complex stroke patterns across multiple scales while maintaining robustness even with limited datasets. The system incorporates preprocessing techniques such as noise reductior-1 and normalization, followed by feature extraction and segmentation to accurately identify stroke regions. Experimental results demonstrate that the proposed model outperforms traditional methods in terms of accuracy, reliability, and efficiency. The developed system serves as a powerful computer-aided diagnosis tool, assisting healthcare professionals in early stroke detection, improved treatment planning, and better patient outcomes.
Disclaimer: Curated by HT Syndication.
