MUMBAI, India, Feb. 13 -- Intellectual Property India has published a patent application (202641008150 A) filed by Srinivas Institute Of Technology, Mangaluru, Karnataka, on Jan. 28, for 'automated pneumonic infiltrate detection via deep convolutional architectures on radiographic imaging.'

Inventor(s) include Mr. Ajay Prinston Pinto; Smita Pandu Naik; Ashwija; Dhruthi Shetty; Kavanashree; Lerina Shynal Dcruz; B V Yashaswini; Sanal; Jithesh B; and Rahul J.

The application for the patent was published on Feb. 13, under issue no. 07/2026.

According to the abstract released by the Intellectual Property India: "The present invention discloses a system and method for the automated detection of pneumonia from chest radiographic images using deep learning techniques, particularly Convolutional Neural Networks (CNNs). The system preprocesses input chest X-ray images by normalizing pixel values and resizing them to standardized dimensions to ensure consistent input for the trained CNN model. The model analyzes radiographic features and classifies the images as indicative of pneumonia or normal, achieving high diagnostic accuracy while minimizing false positives and false negatives. The invention incorporates a user-friendly interface-accessible via web or mobile application-that allows healthcare professionals to upload chest X-rays and receive real-time diagnostic feedback. The backend system integrates cloud-based infrastructure to enable scalable, remote inference and model management. Visual explanations, such as heatmaps generated via class activation mapping, are provided to enhance interpretability and clinical trust. The invention further supports mobile deployment and cloud containerization (e.g., Docker, Kubernetes), enabling use in resource-limited settings and facilitating rapid, wide-scale clinical implementation. This system addresses critical healthcare challenges by offering a reliable, accessible, and efficient solution for early pneumonia detection, thereby improving patient outcomes and reducing the burden of respiratory diseases globally."

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