Rourkela: The National Institute of Technology (NIT) Rourkela added another feather in its cap with researchers from its Biotechnology and Medical Engineering department developing an AI-enabled autofocusing technology that can improve microscopic imaging for biomedical diagnostic applications.
The research team has secured a patent titled ‘A Method for Autofocusing in Optofluidic Microsystems and Processes’ for the technology (Patent number: 589270; Application number: 202431080016).
The research team includes Prof. Earu Banoth, Assistant Professor, Department of Biotechnology and Medical Engineering, NIT Rourkela, and Founder & Director (Non-Executive) of Glowvista Instruments Pvt. Ltd; Dr Shaik Ahmadsaidulu, Research Graduate, NIT Rourkela; NIT Rourkela incubate Amol Lalchand Salve, Design Engineer, and Padmanaban Selvakumar, Product Manager from Glowvista Instruments Pvt. Ltd.
The technology, developed in collaboration with Glowvista Instruments Private Limited, a startup incubated at NIT Rourkela’s Incubator centre (FTBI), is capable of producing rapid, accurate and repeatable results with minimal human intervention.
Microscopy technology is used in research for drug development and point-of-care diagnosis by providing detailed visual information.
Conventional microscopy systems rely on manual adjustments, but they are time-consuming and prone to human errors which can lead to inconsistent results, inaccurate diagnoses and delays in treatment. Such limitations can lead to fatality when dealing with complex biological samples or in cases of emergency diagnostic requirements.
To address these challenges, the NIT Rourkela research team developed an optofluidic digital microscopy platform that uses deep learning technology integrated with an optical imaging system and automated motion control, which allows it to continuously analyse microscopic images in real time and automatically adjust focus through an intelligent feedback mechanism.
The system, developed at a cost of Rs 1.20 lakh, showed accurate results in detecting Acute Lymphoblastic Leukemia (Blood Cancer), malaria, and Complete Blood Cells counts through blood cell classification (5-class and 7-class categorization).
“Our target is to develop a simple handheld system that should work as effectively as imported automated microscopy technology with precise information. Further, the system should be extended for various applications, unlike Flow Cytometers and Imaging Flow Cytometers,” Dr Banoth said.
The system has been developed with research grants from the Anusandhan National Research Foundation (ANRF), Department of Science and Technology (DST), and Department of Biotechnology (DBT), Government of India.
Key features of the system:
* AI-powered intelligent autofocus with real-time image processing.
* Automated motion control for precise focus adjustment.
* Enhanced imaging of complex biological and micro-scale samples.
* Cloud-enabled learning for continuous performance improvement.
* User-friendly operation with improved accuracy, repeatability, and efficiency.
Technology has potential applications in:
* Biomedical diagnostics and disease detection
* Digital pathology and tissue imaging
* AI-assisted microscopy and automated imaging
* Point-of-care healthcare devices
* Microfluidic analysis and biofluid monitoring
* Biomedical and Life sciences research
* Smart laboratory automation
* Portable and remote diagnostic systems.
On the next steps of this research, Prof. Banoth said, “We are extending our work to develop complete ground truth data as well as scale up the work for deployment at various locations for field testing and to obtain feedback from diagnostic centres and research laboratories. The data will be used for further approvals towards developing a market-ready product, and we look forward to its market launch. At present, we are looking for funding support from both the research and startup sides to scale up the work.”
