Medical Image Viewing Platform to Integrate with Google Cloud

The underlying imaging technology allows medical professionals to engage in interactive, web-based reviews, on any device, using full fidelity digital imaging and communications in medicine (DICOM) images. IMS also plans to optimize the global reach of Google Cloud Platform and expand its current serverless viewing technology in parallel with its artificial intelligence (AI) and machine learning initiatives.

Features include intuitive imaging tools, hanging protocols, presets, and customized toolbars that facilitate image uploading, viewing, annotation, saving, and exporting. Uploaded studies of interest can be immediately downloaded for instant viewing, with all annotations and markups saved and displayed immediately, and can also be shared with colleagues with a quick email link. A full tool set enables quick content creation, including for educational purposes, such as quiz-style multiple choice, true/false, anatomical, or informative questions alongside full-resolution medical images.

“Clients tell us that they like IMS Cloud View because our technology is the missing piece that completes the viewer value chain. It is simple to use, reliable in all types of network conditions, and gives them the freedom and flexibility to read, assess, mark-up and save, import, share, and send secure links from any device, anytime, anywhere,” said Vittorio Accomazzi, CTO of IMS. “They maintain ownership of their data in Google Cloud and we store it in a DICOM compliant, non-proprietary way. We believe IMS Cloud View and Google Cloud Platform will revolutionize the medical imaging industry.”

Google Cloud Platform is a suite of cloud computing services that provides infrastructure as a service, platform as a service, and serverless computing environments. It runs on the same infrastructure that Google uses internally for its end-user products, such as Google Search and YouTube. Alongside a set of management tools, it provides a series of modular services including computing, data storage, data analytics, and machine learning.

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