Google Cloud on Tuesday announced the Medical Imaging Suite, a new technology it says can help with the accessibility and interoperability of radiology and other imaging data.
BECAUSE IT IS IMPORTANT
The new suite includes components focused on storage, lab, datasets, dashboards, and AI pipelines for images, according to Google Cloud.
It is designed to offer flexible options for cloud, on-premises, or edge deployment to enable organizations to meet various sovereignty, data security, and privacy requirements, officials say, while providing centralized management and enforcement. of policies with Google Distributed Cloud, enabled by Anthos.
Google’s Cloud Healthcare API enables secure data exchange using the DICOMweb international 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-premises data management to the cloud, and Change Healthcare’s cloud-native enterprise image PACS. In addition, AI-assisted annotation tools from NVIDIA and MONAI can help automate the repetitive, manual task of labeling medical images, the company says.
Provider organizations can use BigQuery and Looker to view and search petabytes of image data to perform advanced analytics and build training data sets with no operational overhead, according to the product announcement.
Meanwhile, Vertex AI on Google Cloud can accelerate the development of AI pipelines to build scalable machine learning models, with 80% fewer lines of code required for custom modeling.
THE BIGGEST TREND
Google notes that imaging data accounts for up to 90% of all healthcare data, and the volume only increases the workload for radiologists and other healthcare professionals tasked with manually interpreting these images for doctors and patients.
AI can help support faster and more accurate diagnostic imaging and increase provider productivity and patient outcomes, according to Google, which points to two customers already using the Medical Imaging Suite.
At Hackensack Meridian Health, New Jersey’s largest health system, doctors are using technology to de-identify petabytes of images. The goal is to soon build AI algorithms to predict metastasis in prostate cancer patients.
“We are working to develop AI capabilities that will support image-based clinical diagnosis across a variety of images and will be an integral part of our clinical workflow,” Sameer Sethi, director of data and analytics at Hackensack Meridian Health, said in a statement. a statement. .
“Google Cloud imaging capabilities, including standardized storage and de-identification, help us unlock the value of our imaging data so clinicians and researchers are equipped with digitized decision support that fits their clinical workflow.” “, 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 diagnostic system,” said Michael Quick, vice president of research and development innovation at Hologic.
“By complementing our diagnostic and AI expertise with Google Cloud’s expertise in artificial intelligence, deep learning, and its cloud-based technologies for image storage, we’re evolving our technologies to improve lab performance, healthcare providers and patient care.”
IN THE REGISTRY
“Google pioneered the use of artificial intelligence and machine vision in Google Photos, Google Image Search and Google Lens, and now we’re making our imaging expertise, tools and technologies available to healthcare and life sciences companies,” Alissa Hsu Lynch, Global Lead of MedTech Strategy and Solutions at Google Cloud, said in a statement. “Our medical imaging suite shows what’s possible when technology and healthcare companies come together.”
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Healthcare IT News is published by HIMSS.