By Prarthana Mitra
At an event organised by the American Association for Cancer Research in Chicago on Monday, researchers from Google presented a microscope prototype that makes use of augmented reality (AR), and machine learning to analyse and diagnose potentially cancerous cells.
What is more, the microscope has been designed to detect the presence of cancer in real-time, which will likely save precious time in the race to save lives.
Here’s what happened
The modified microscope looks like any other that you may have seen in a pathology lab, except that it comes equipped with a neural network, which is reprogrammed to detect the presence of cancerous cells in images of human tissue.
When a slide with human tissue is placed beneath the microscope, the image feed of the slide is simultaneously projected onto a computer screen. Next, AI algorithms then analyse the image, highlighting any cancer cells found, and outlining them in the image seen by the scientist through the microscope’s eye piece.
Besides the real-time image analysis, the microscope’s ability to channel the results of multi-level algorithms directly to the its field of view is its real remarkable.
“In principle, the ARM [Augmented Reality Miscroscope] can provide a wide variety of visual feedback, including text, arrows, contours, heat maps or animations, and is capable of running many types of machine learning algorithms aimed at solving different problems such as object detection, quantification or classification,” Martin Stumpe, and Craig Mermel from Google’s Brain Team, wrote in a blog.
Why you should care
The first to introduce AR goggles in 2015, Google’s decision to expand the scope of AR from lifestyle to healthcare is fuelling groundbreaking research. Today, the amalgamation of machine learning and medical tech, big data and biology, has resulted in an integration of technology and medicine—vision correction surgeries conducted via AI-powered laser machines, and machine learning-powered prosthesis devices are only the tip of the iceberg.
Once perfected, the ARM’s potential to save millions of lives is not lost on the developers, who wish to end the predominant trend of direct tissue visualisation using compound microscopes, by replacing them with Google’s next-gen device. Using AI-based deep learning tools, this microscope is believed to be capable of accelerating, and democratising the adoption of digital health options in pathology.
The ARM can also be retrofitted to any ordinary light microscope, making it possible for groups with limited funds, such as small labs, and clinics in developing countries to benefit from this cutting-edge technology. Simple, inexpensive, and easy to use, the microscope has so far, been successful in providing correct assessments for prostate and breast cancer metastases.
Google plans to extend its scope to other deadly diseases like tuberculosis and malaria, as well as adapt it “for a broad range of applications across healthcare, life sciences research and material science.”
“We’re excited to continue to explore how the ARM can help accelerate the adoption of machine learning for positive impact around the world,” Stumpe and Mermel concluded in their post.
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