MUMBAI, India, Aug. 29 -- Intellectual Property India has published a patent application (202441013559 A) filed by Chaitanya Bharathi Institute Of Technology, Department Of Information Technology, Hyderabad, Telangana, on Feb. 25, 2024, for 'the x-ray whisperer: deep learning for automated medical image interpretation and early disease detection.'

Inventor(s) include Dr. Rajanikanth Aluvalu; Dr. R. Madana Mohana; Dr. Uma Maheswari V; and Dr. Padmavathi Vurubindi.

The application for the patent was published on Aug. 29, under issue no. 35/2025.

According to the abstract released by the Intellectual Property India: "The technique of taking pictures of inside organs for therapeutic purposes, such identifying or researching disorders, is known as medical imaging. Enhancing the effectiveness of clinical research and treatment choices is the main goal of medical image analysis. Medical image analysis has been completely redesigned using deep learning, which produces outstanding results for image processing tasks including feature extraction, registration, segmentation, and classification. The primary drivers behind this are the comeback of deep convolutional neural networks and the availability of processing resources. Deep learning methods are effective in identifying hidden patterns in pictures and helping medical professionals make the precise diagnosis. It has shown to be the most successful technique for computer-assisted diagnosis, illness classification, organ segmentation, and cancer detection. Numerous deep learning techniques have been described for the analysis of medical pictures for different types of diagnosis. In this study, we evaluate the research that makes use of the most recent advancements in deep learning techniques for medical image processing. We start the survey by summarizing convolutional neural network-based medical imaging research projects. Second, we go [501] over widely used pretrained models and generic adversarial networks that can boost the efficiency of convolutional networks."

Disclaimer: Curated by HT Syndication.