Google Cloud’s New Interoperable Medical Imaging Suite
Google Cloud dropped its new medical imaging suite that combines artificial intelligence, cloud storage, and machine learning to help providers build their own algorithms for identifying cancers.
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By - On Tuesday, Google Cloud revealed its new Medical Imaging Suite that combines the accessibility of its cloud-based platform with a wide array of machine learning and artificial intelligence (AI) tools. The suite will serve as a workshop for provider organizations looking to create their own intelligent medical imaging tools.
The platform includes an imaging lab with built-in AI-assisted annotation capabilities from NVIDIA and MONAI that will reduce repetitive tasks for radiologists. The Medical Imaging Suite will provide clients with “petabytes of imaging data” for organizations that want to create training datasets or practice advanced analytics. According to the press release, Google’s Vertex AI, which is included in the Medical Imaging Suite, will allow organizations to utilize shared sets of deidentified images to build their own machine-learning models.
Google’s industry solution also offers interoperable image storing and data exchange through its Cloud Healthcare API, allowing users to move data from on-premise storage to the Cloud safely and privately.
"Google pioneered the use of AI and computer vision in Google Photos, Google Image Search, and Google Lens, and now we're making our imaging expertise, tools, and technologies available for healthcare and life sciences enterprises," said Alissa Hsu Lynch, Global Lead of Google Cloud's MedTech Strategy and Solutions in the press release. "Our Medical Imaging Suite shows what's possible when tech and healthcare companies come together."
Google and Hackensack Meridian Health have already begun to implement the Medical Imaging Suite as they work to create their own algorithm for predicting prostate cancer. "We are working toward building AI capabilities that will support image-based clinical diagnosis across a range of imaging and be an integral part of our clinical workflow," said Sameer Sethi, SVP and chief data and analytics officer at Hackensack Meridian Health, in Google’s press release. "Google Cloud's imaging capabilities, including standardized storage and de-identification, are helping us unlock the value of our imaging data, so clinicians and researchers are equipped with digitized decision support that fits into their clinical workflow.”
Another medical technology company, Hologic, has been working with Google to enhance its digital diagnostics. Using the Medical Imaging Suite, Hologic has refined its AI algorithm for identifying precancerous lesions and cervical cancer.
Already, at least one-third of hospitals and radiologists in the United States are using AI to deidentify images and create algorithms for cancer detection. Analysts now expect the precision medical imaging market to be worth more than $8 billion by 2027.
The field is primed for growth, and major provider organizations and technology vendors have paired up to build their AI-enhanced platforms. Mayo Clinic and Visage Imaging are involved in a multiyear deal to develop end-to-end AI solutions for medical imaging. Meanwhile, the University of San Francisco and NVIDIA have partnered to create the Center for Intelligent Imaging, which will build tools and apply AI to the study of medical imaging.
