MUMBAI, India, Jan. 9 -- Intellectual Property India has published a patent application (202541124918 A) filed by Manipal Academy Of Higher Education, Manipal, Karnataka, on Dec 10 for 'a system and method for automated identification and quantification of histological structures using deep learning.'
Inventor(s) include Megha Nagaraj Nayak; Ali Murtaza Rizvi; R. Vinoth; Ravindra Prabhu Attur; Vinod C. Nayak; Sushma Prabhath; and Deepak Nayak M.
The application for the patent was published on Jan. 9, under issue no. 02/2026.
According to the abstract released by the Intellectual Property India: "The invention discloses a system and method for automated identification and quantification of histological structures using deep learning, specifically for glomerulus detection in kidney tissue images. The system comprises a data collection module for acquiring histological images, an annotation and labeling module for creating ground truth data, and an environment setup and preprocessing module for preparing the data. Deep learning models, including YOLOv3, YOLOv5, and YOLOv7, are implemented in the deep learning model module to detect glomeruli. The testing and optimization module evaluates and optimizes the models, with the best-performing model being deployed via the deployment and user interface module. The output and visualization module presents the results, including bounding boxes around detected glomeruli and nephron counts. The system enables automated, efficient, and accurate analysis of kidney tissue, aiding in diagnosis and research."
Disclaimer: Curated by HT Syndication.
