NIT Rourkela develops AI-powered microscopy for disease detection

The AI-enabled microscopy platform can rapidly detect blood cancer and malaria while improving imaging precision and reducing human intervention in diagnostics

In a remarkable innovation, researchers at the National Institute of Technology (NIT), Rourkela have developed an artificial intelligence (AI)-enabled autofocusing technology that could significantly improve microscopic imaging for biomedical diagnostics.

 

The system has already demonstrated promising lab-scale results in detecting acute lymphoblastic leukaemia (blood cancer) and malaria, marking a significant step towards affordable next-generation healthcare diagnostics in India.

 

Developed in collaboration with Glowvista Instruments Private Limited, a startup incubated at NIT Rourkela’s Incubator Centre (FTBI), the new technology is capable of producing rapid, accurate, and repeatable results with minimal human intervention. The research team has secured a patent for the technology.

 

Microscopy technology plays a crucial role in healthcare diagnostics by enabling doctors and researchers to study cells, tissues, microorganisms, and other biological structures that are invisible to the naked eye. It is widely used for identifying cancers, infectious diseases such as malaria and tuberculosis, pathology-related disorders, and also supports drug development and point-of-care diagnostics.

 

However, conventional microscopy systems largely depend on manual focusing, making them time-consuming and vulnerable to human error, often resulting in inconsistent imaging, inaccurate diagnoses, and delays in treatment. Such limitations can become fatal when dealing with complex biological samples or in cases of emergency diagnostic requirements.

 

Earu Banoth, assistant professor at NIT Rourkela and founder-director (non-executive) of Glowvista Instruments Pvt Ltd, said an optofluidic digital microscopy platform has been developed to address the longstanding limitations in conventional microscopy systems.

 

“The optofluidic digital microscopy platform combines deep-learning algorithms with optical imaging systems and automated motion control. The intelligent system continuously analyses microscopic images in real time and automatically adjusts focus through an AI-driven feedback mechanism, improving imaging precision and efficiency,” he said.

 

Built at a cost of around Rs 1.2 lakh, the system demonstrated promising results during laboratory testing. Besides detecting acute lymphoblastic leukaemia and malaria, it also successfully carried out complete blood cell counts through five-class and seven-class blood cell categorisation.

 

Explaining the broader objective of the project, Banoth said the team is working towards developing a simple handheld system that can perform at par with expensive imported automated microscopy technologies while offering precise diagnostic information. “The technology is also being designed for wider biomedical applications beyond the capabilities of conventional flow cytometers and imaging flow cytometers,” he said.

 

The developed system incorporates several advanced features, including AI-powered intelligent autofocus with real-time image processing, automated motion control for precise focus adjustment, enhanced imaging of complex biological samples, cloud-enabled learning for continuous improvement, and user-friendly operation with improved repeatability and efficiency.

 

According to the researchers, the technology has potential applications across a broad spectrum of healthcare and life sciences fields, including biomedical diagnostics, digital pathology, AI-assisted microscopy, automated imaging, point-of-care healthcare devices, biofluid monitoring, smart laboratory automation, and portable remote diagnostic systems.

 

“We are now working on generating larger ground-truth datasets and scaling up the system for field deployment in diagnostic centres and research laboratories. Feedback from field trials will be used to refine the technology and secure approvals for commercial deployment,” said Banoth.

 

The researchers are also seeking additional support from research and startup ecosystems to accelerate the development of a market-ready product. Other members of the team include Shaik Ahmadsaidulu, research graduate; Amol Lalchand Salve, design engineer; and Padmanaban Selvakumar, product manager, from Glowvista Instruments Pvt Ltd.

 

The research has received funding support from the Anusandhan National Research Foundation (ANRF), Department of Science and Technology (DST), and the Department of Biotechnology (DBT) under the Government of India.