The research team, along with industry collaborators, have developed AI-based algorithms that enables the device to undertake automatic screening
Indian Institute of Technology Mandi Researchers have contributed in developing an artificial intelligence-powered point-of-care device to screen for cervical cancer by analysing microscopy images with high accuracy. This project has been taken up in collaboration with Aindra Systems, Bengaluru.
The research was undertaken by a team led by Dr Anil Sao and Dr Arnav Bhavsar, Associate Professors, School of Computing and Electrical Engineering, IIT Mandi with their research scholars Srishti Gautam and Krati Gupta. The team, along with the industry collaborators, has developed AI-based algorithms that enables the device to undertake automatic screening for cervical cancer.
Speaking about the practical advantages of the device created during the research, Dr Bhavsar said, “The difference between a conventional system and Aindra’s point-of-care system is that, the latter is portable and can be taken to the potential patients. In the conventional system, the people have to visit the pathology laboratory to get themselves screened.”
Adarsh Natrajan, Chief Executive Officer, Aindra Systems, Harinarayanan KK, Head of Research, Aindra Systems and Nirmal Jith, Data Scientist (Formerly at Aindra Systems) collaborated on the design and the development of the device.
They have applied for an international patent for the device and algorithm in 2016 and their research results have been published in many international journals and conference proceedings in the past two years. The device prototypes are currently undergoing clinical testing at Kidwai Memorial Hospital, Bengaluru, Manipal Hospital, Karnataka and Raja Rajeswari Medical College and Hospital, Bengaluru. The accuracy of the developed prototypes has been consistently around 88 per cent.
The IIT Mandi team first analysed Pap smear images provided by the industrial partner, Aindra, and characterised them into ‘normal’ and ‘potentially cancerous.’ They developed a computer programme that could differentiate between the two.
“We could demonstrate performance improvements over some of the contemporary methods, with relatively simpler and arguably more efficient methods,” said Dr Bhavsar.
The developed algorithm is based on the recent deep learning paradigm of artificial intelligence. The advantage of this type of programme is that it can be used in situations where in one can encounter a large amount and variability in data.
Speaking on the relevance and importance of this algorithm and device, Dr Sao said, “Given the shortage of pathologists in India, these algorithms will help in automating the process of screening Pap -Smear images. Thus, there will be a significant reduction in time spent by the pathologist, thereby reducing cost and improving the screening accuracy.”