NTT Data platform applies analytics, AI to images within workflows

An imaging services vendor is beefing up its offerings to enable radiologists to apply analytics and artificial intelligence while they are assessing patient images.

New offerings from NTT Data Services reflect current efforts within the image assessment process to interject additional computing intelligence to help find anomalies and diagnose problems quickly.

NTT Data says its unified clinical analytics and management platform is intended to integrate imaging analytics in the workflows of clinical teams and radiologists.

Pressure is increasing for radiologists to improve performance under emerging value-based care pressures to improve quality while reducing imaging utilization, says Barron Lang, vice president of healthcare and life sciences for NTT DATA Services.

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A technician looks at scanned imagery in the control room of the diagnostic imaging area at the Hong Kong Integrated Oncology Centre in Hong Kong, China, on Tuesday, Nov. 3, 2015. Equipped with biopsy facilities, body scanners, and quiet 'VIP' chemotherapy rooms, the Hong Kong Integrated Oncology Centre is the first of a string of such facilities that TE Asia Healthcare Partners, a portfolio company funded by TPG Capital, is planning in Asia. Photographer: Xaume Olleros/Bloomberg

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The new platform enables providers to apply algorithms from other vendors with which NTT Data has partnerships. It integrates a reporting tool in any picture archiving and communication system workstation, with annotated images; drop images into a desktop engine that allows specific artificial intelligence engines to execute; and integrates reports into dictation solutions to provide annotated series and standardized DICOM-structured reports.

NTT Data is also partnering with MD.ai to beef up artificial intelligence capabilities within its radiology platform, with the intent of enabling provider organizations to improve the quality of interpretation and derive more insights from imaging studies.

MD.ai offers semi-automated tools for imaging research, collaborative data annotation software as well as web-based algorithms to facilitate the adoption of AI by healthcare organizations. In addition, MD.ai facilitates research by enabling customers to participate in the development of anonymized datasets that can be used to validate AI algorithms.

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