Google Augmented-Reality Microscope Helps Detect Cancer
Google introduced an augmented reality microscope prototype that could be used to help doctors detect cancer and make other diagnoses, the tech website Engadget reported.
Google researchers said at the annual meeting of the American Association of Cancer Research that its microscope could “possibly help accelerate and democratize the adoption of deep learning tools for pathologists around the world,” regardless of their budget and where they are located, Engadget wrote.
The researchers said the current method of analyzing biological tissue to see if there are signs of cancer, how much and what kind can be time consuming. The augmented reality microscope could make such efforts feasible for small labs and clinics, or developing countries.
Google said it would use artificial intelligence technology to detect cancer cells in images of human tissue and place it under a modified microscope that uses augmented reality and the AI technology, Engadget wrote. The technology’s algorithms can then detect the cancer and outline the images through the eyepiece of the microscope.
“In principle, the (augmented reality microscope) can provide a wide variety of visual feedback, including text, arrows, contours, heatmaps, 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, technical lead and Craig Mermel, product manager for the Google Brain Team, said in a blog post Monday about the talk.
“As a demonstration of the potential utility of the ARM, we configured it to run two different cancer detection algorithms: one that detects breast cancer metastases in lymph node specimens, and another that detects prostate cancer in prostatectomy specimens,” Stumpe and Mermel continued.
They said the microscope could have a “large impact on global health,” including the diagnosis of infectious diseases, including tuberculosis and malaria, in developing countries.
“Furthermore, even in hospitals that will adopt a digital pathology workflow in the near future, ARM could be used in combination with the digital workflow where scanners still face major challenges or where rapid turnaround is required,” the researchers wrote.
“Of course, light microscopes have proven useful in many industries other than pathology, and we believe the ARM can be adapted 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 continued.
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