Aimed at helping radiologists and imaging departments across hospitals, the three products launched are, Access CT 32 Slice, Ingenia Prodiva 1.5T MRI and Dura Diagnost F30 Digital X-ray.
Rohit Sathe, president of Philips Healthcare, India, said , “Philips has always been focussing on the emerging workflow and diagnostic needs of radiologists in India, by developing meaningful innovations in imaging.The new offerings in MRI, CT and Digital X-ray are developed to help radiologists diagnose faster, more accurately with added benefit of lower ownership costs and better patient experience. I am sure that these solutions will effectively meet the expectations of the radiologists and imaging departments”.
Philips’ Access CT 32 Slice is designed to provide flexibility and superior quality images. An added benefit is the accurate diagnosis it provides at a lower cost of ownership. Ingenia Prodiva 1.5T MRI on the other hand, has already been installed in over 2,000 places across the globe. It is based on the tested dStream digital broadband technology and comes with a Breeze Workflow guided patient setup. Philips’ third AI-based healthcare product is the DuraDiagnost F30 Digital X-ray, which enables improved clinical judgements and reduces the burden on imaging personnel.
The influx of artificial intelligence into diagnosis of diseases and AI-aided medical devices that facilitate improved healthcare is slowly on the rise in India.
It was reported recently that Apex Heart Institute in Ahmedabad became the first location outside the US to have a commercial installation of the advanced AI-powered vascular robotic system, CorPath GRX. Produced by Corindus Vascular Robotics, the robotic arm costs $1.5 million and possess an in-built AI that enables cardiologists in making informed clinical decisions.
Towards the end of 2017, it was reported that researchers from the Indian Institute of Technology, Kanpur (IIT-K) and Indian Institute of Science Education and Research, Kolkata (IISER-K) and had developed an algorithm based on the light scattering properties of healthy and precancerous cells. Using the principal of minute difference in the refractive index of light between the healthy and cancerous cells, the researchers developed an AI-based algorithm that could not only discern the difference difference between healthy and precancerous tissue, but can also identify the different progressive stages of the disease with an accuracy of over 95 percent