Rathish
Author – Ritesh Ranjan: Researchers at the National Institute of Technology, Rourkela have developed an AI-enabled microscopy technology that could make biomedical diagnosis faster, more accurate and more accessible. The innovation uses artificial intelligence, deep learning and automated focus control to improve microscopic imaging, especially for disease detection and blood cell analysis.
The technology has been developed in collaboration with Glowvista Instruments Private Limited, a startup incubated at NIT Rourkela’s Foundation for Technology and Business Incubation, also known as FTBI. The project is aimed at reducing human dependency in microscopy-based diagnosis while improving the speed, consistency and reliability of test results.
Microscopy is one of the m
ost important tools in medical diagnostics. It is widely used for studying blood samples, tissue samples, microorganisms and disease indicators. However, traditional microscopy often depends heavily on manual focusing and expert observation. This can make the process time-consuming and sometimes inconsistent, especially in busy diagnostic labs or areas with limited access to trained professionals.
NIT Rourkela’s AI-enabled autofocusing system attempts to solve this challenge by combining optical imaging with intelligent automation.
A Patent-Backed Biomedical Innovation
The innovation has already secured a patent titled “A Method for Autofocusing in Optofluidic Microsystems and Processes.” The patent number is 589270, and the application number is 202431080016.
This patent-backed development gives the technology a strong foundation for future product development, commercialization and wider adoption in healthcare settings. Patent protection is especially important for deep-tech medical innovations because it supports research continuity, industry collaboration and long-term scalability.
The system is designed as an optofluidic digital microscopy platform. In simple terms, it brings together optics, fluid-based sample handling and digital image processing to capture and analyse microscopic images more effectively.
How the AI-Enabled Microscopy Technology Works
The technology uses deep learning and automated motion control to focus microscopic images without the need for repeated manual adjustments. In a conventional microscope, a user often has to adjust the focus manually to get a clear image. This process can be slow and may vary from person to person.
In the new system, microscopic images are continuously analysed in real time. The AI model studies the image quality and sends feedback to the motion control system. Based on this feedback, the microscope automatically adjusts the focus until the image becomes clear.
This intelligent feedback mechanism helps reduce human error and improves repeatability. It also allows the system to process samples faster, which can be extremely useful in medical diagnosis where timely results matter.
For example, in diseases like malaria or blood cancer, accurate microscopic examination can help doctors detect abnormalities early. If the image is blurred or poorly focused, important diagnostic details may be missed. Automated focusing can therefore improve the quality of analysis and support better medical decision-making.
Applications in Disease Detection
During lab-scale testing, the system showed promising results in detecting Acute Lymphoblastic Leukemia, malaria and complete blood cell counts. It was also able to support blood cell categorization using 5-class and 7-class classification methods.
These results indicate that the technology could be useful in several areas of biomedical diagnostics, including:
Digital pathology, where tissue and cell images are analysed digitally
Blood sample analysis for identifying abnormalities
Malaria detection through microscopic examination
Blood cancer screening and research
Point-of-care diagnostic systems
Microfluidic analysis and biofluid monitoring
Research laboratories and medical imaging studies
The ability to support multiple diagnostic applications makes the system highly valuable. Instead of being limited to one disease or one type of sample, the platform can potentially be adapted for different biomedical use cases.
Why Automated Focus Control Matters
Manual focusing is one of the most common challenges in microscopy. Even skilled professionals may take time to adjust the image properly, especially when handling multiple samples. In large diagnostic centres, this can slow down the workflow.
In rural or resource-limited areas, the challenge can be even greater because trained microscopy experts may not always be available. An AI-enabled autofocusing system can help reduce this dependency by making the process more automated and user-friendly.
Better focus also means better image quality. In diagnostics, image quality directly affects the accuracy of analysis. A clear image can help identify disease markers more reliably, while an unclear image may lead to delays or incorrect interpretation.
By automating focus control, NIT Rourkela’s technology can make microscopy more consistent, faster and easier to use.
A Low-Cost Innovation with High Impact
One of the most impressive aspects of this development is its affordability. The prototype was built at an estimated cost of around Rs. 1.20 lakh. This is significant because advanced automated microscopy systems and imaging technologies are often expensive, especially when imported.
A low-cost, AI-powered microscopy system can be highly beneficial for India’s healthcare ecosystem. Many hospitals, diagnostic centres and research labs need advanced imaging solutions but may not have the budget for high-end imported equipment.
According to Dr. Earu Banoth, the goal is to develop a simple handheld system that can perform effectively while remaining affordable. The team also wants the device to be adaptable for a wider range of applications compared to tools such as flow cytometers and imaging flow cytometers.
This makes the innovation especially relevant for India, where healthcare technology must often balance quality, affordability and scalability.
Supporting Make in India Healthcare Technology
The development aligns well with India’s broader focus on indigenous innovation and the Make in India initiative. Instead of depending only on imported diagnostic systems, Indian institutions and startups are working together to build locally developed technologies for real-world healthcare challenges.
NIT Rourkela’s collaboration with Glowvista Instruments Private Limited is a strong example of how academic research and startup innovation can come together. Such partnerships can help move laboratory prototypes closer to market-ready products.
The project has received support from the Anusandhan National Research Foundation, Department of Science and Technology and Department of Biotechnology, Government of India. This support plays an important role in helping researchers develop, test and scale advanced biomedical technologies.
Research Team Behind the Innovation
The project team includes Prof. Earu Banoth, Dr. Shaik Ahmadsaidulu, Mr. Amol Lalchand Salve and Mr. Padmanaban Selvakumar.
Their work highlights the growing role of engineering institutions in healthcare innovation. Today, biomedical diagnosis is not only a medical field but also an interdisciplinary area involving electronics, artificial intelligence, optics, automation, data science and biotechnology.
By combining these fields, the team has developed a system that could contribute to smarter and more accessible diagnostic solutions.
Importance for Healthcare Diagnosis
AI-enabled microscopy has the potential to improve diagnosis in situations where speed and accuracy are critical. For conditions such as malaria and blood cancer, early detection can make a major difference in treatment outcomes.
In many cases, diagnosis depends on identifying small changes in cells or biological samples. A system that can produce clearer images and analyse them more consistently can help doctors and lab professionals make faster decisions.
The cloud-enabled learning feature of the system also adds long-term value. As more data is added, the system can continue to learn and improve. This opens the possibility of remote diagnostics, smart laboratory automation and AI-assisted healthcare networks.
In the future, such technologies could be used in diagnostic centres, hospitals, mobile healthcare units and field testing environments.
Next Steps for the Technology
The researchers are now working on building complete ground truth data, which is essential for improving the accuracy of AI-based diagnosis. Ground truth data helps train and validate AI models by providing confirmed reference results.
The team also plans to scale the technology for field testing and collect feedback from diagnostic centres and research laboratories. These steps are important before the system can move toward regulatory approval and commercial launch.
Field testing will help the researchers understand how the device performs in real-world conditions. Feedback from healthcare professionals will also help improve usability, accuracy and workflow integration.
Conclusion
NIT Rourkela’s AI-enabled microscopy technology is a promising step toward faster, smarter and more affordable biomedical diagnosis. By using deep learning, automated focus control and optofluidic imaging, the system can reduce manual effort and improve the quality of microscopic analysis.
Its ability to support disease detection, blood cell categorization, digital pathology and point-of-care diagnosis gives it strong potential for healthcare and research applications. With a prototype cost of around Rs. 1.20 lakh, the innovation also shows that advanced medical technology can be developed affordably in India.
As the researchers move toward field testing and product development, this patent-backed system could become an important milestone in India’s journey toward indigenous, AI-powered healthcare solutions.
FAQs
1. What has NIT Rourkela developed?
NIT Rourkela researchers have developed an AI-enabled autofocusing microscopy technology for biomedical diagnosis. The system uses deep learning and automated focus control to improve microscopic imaging and reduce manual intervention.
2. Which diseases can this AI-enabled microscopy system help detect?
In lab-scale testing, the system showed accurate results in detecting Acute Lymphoblastic Leukemia, malaria and complete blood cell counts through blood cell categorization.
3. What is the patent related to this innovation?
The innovation has secured a patent titled “A Method for Autofocusing in Optofluidic Microsystems and Processes”, with Patent No. 589270 and Application No. 202431080016.
4. Why is this technology important for healthcare?
The technology can improve image clarity, reduce human error, speed up diagnosis and support more reliable analysis. It can be useful in hospitals, diagnostic centres, research labs and point-of-care healthcare settings.
5. How much did the prototype cost?
The prototype was developed at an estimated cost of around Rs. 1.20 lakh, making it a low-cost alternative to many expensive imported automated microscopy systems.