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Samsung's X-Ray Devices to Be Powered by Lunit AI Solutions for Advanced Chest Screening

By MedImaging International staff writers
Posted on 17 Jan 2024
Image: The Lunit INSIGHT CXR AI-powered chest X-ray analysis solution (Photo courtesy of Lunit)
Image: The Lunit INSIGHT CXR AI-powered chest X-ray analysis solution (Photo courtesy of Lunit)

Samsung Healthcare (Suwon, South Korea) and Lunit (Seoul, South Korea) have entered into a collaboration to integrate Lunit's AI technology into Samsung's premium X-ray devices, enhancing the accuracy and speed of chest screening.

Under the terms of the three-year supply contract, Lunit will provide two AI-powered chest screening solutions: Lunit INSIGHT CXR and Lunit INSIGHT CXR Triage to Samsung. INSIGHT CXR is an AI-powered chest X-ray analysis solution with the capability to detect 10 of the most common lung abnormalities, including lung cancer, pneumonia, and pneumothorax. INSIGHT CXR Triage is an FDA-cleared AI solution that can identify pre-specified critical findings, such as pleural effusion or pneumothorax, on frontal chest X-ray images. The software then flags the images in the Picture Archiving and Communication System (PACS) workstation, enabling a prioritized review process for timely intervention.

Given the urgency of cases generally experienced in Intensive Care Units (ICUs) and Emergency Rooms (ERs), Samsung’s X-ray devices with the Lunit INSIGHT CXR Triage will be mainly deployed in these high-stakes medical settings. During the initial phase of this collaboration, Samsung’s X-ray devices integrated with Lunit's AI solutions will target markets in the US, Canada, and Europe. In the future, the availability of these devices will be expanded to the Middle East, South America, and Southeast Asia, thus broadening their global reach.

"The synergy between Lunit and Samsung Electronics will enable faster, more accurate chest screenings, leading to timely interventions and improved patient outcomes," said Brandon Suh, CEO of Lunit. “We're excited about the potential this partnership holds for advancing chest X-ray practices, particularly in ICUs and ERs.”

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Image: Researchers develop a vision-language model trained on large-scale data to generate clinically relevant findings from chest computed tomography images through visual question answering (Ms. Maiko Nagao from Meijo University, Japan)

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