Google Cloud on Tuesday announced Medical Imaging Suite, new technology it says can help with accessibility and interoperability of radiology and other imaging data.
WHY IT MATTERS
The new suite includes components focused on storage, lab, datasets, dashboards and AI pipelines for imaging, according to Google Cloud.
It’s designed to offer flexible options for cloud, on-prem or edge deployment to allow organizations to meet diverse sovereignty, data security, and privacy requirements, buy precose prices officials say, while providing centralized management and policy enforcement with Google Distributed Cloud, enabled by Anthos.
Google’s Cloud Healthcare API enables secure data exchange using the international DICOMweb standard for imaging and offers a scalable, enterprise-grade development environment and includes automated DICOM de-identification.
Other technology partners include NetApp for seamless on-prem to cloud data management, and Change Healthcare’s cloud-native enterprise imaging PACS. In addition, AI-assisted annotation tools from NVIDIA and MONAI can help automate the manual and repetitive task of labeling medical images, the company says.
Provider organizations can use BigQuery and Looker to view and search petabytes of imaging data to perform advanced analytics and create training datasets with zero operational overhead, according to the product announcement.
Meanwhile, Vertex AI on Google Cloud can accelerate development of AI pipelines to build scalable machine learning models, with 80% fewer lines of code required for custom modeling.
THE LARGER TREND
Google notes that imaging data accounts for as much as 90% of all healthcare data, with the volume only increasing the workload for radiologists and other healthcare professionals tasked with manually interpreting these images for clinicians and patients.
AI can help support faster, more accurate diagnosis of images and boost productivity for providers and outcomes for patients, according to Google, which points to two customers already using Medical Imaging Suite.
At Hackensack Meridian Health, New Jersey’s largest health system, clinicians are using the technology to de-identify petabytes of images. The goal is to soon build AI algorithms to predict metastasis in patients with prostate cancer.
“We are working towards 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, chief data and analytics officer at Hackensack Meridian Health, in a statement.
“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,” he said.
And vendor Hologic, developer of a digital platform to help cytologists and pathologists identify precancerous lesions and cervical cancer cells in women, plans to expand its capabilities using the Medical Imaging Suite.
“We’ve partnered with Google Cloud to use the Medical Imaging Suite to enhance our current Genius Digital Diagnostics System,” said Michael Quick, vice president of research and development innovation at Hologic.
“By complementing our expertise in diagnostics and Al with Google Cloud’s expertise in AI, deep learning, and its cloud-based technologies for imaging storage, we’re evolving our technologies to improve laboratory performance, healthcare provider decision-making, and patient care.”
ON THE RECORD
“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 a statement. “Our Medical Imaging Suite shows what’s possible when tech and healthcare companies come together.”
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