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Fujitsu Laboratories has developed a technology to retrieve similar disease cases from a computed tomography (CT) database of previously taken images.
The technology, jointly developed with Fujitsu R&D Center Co, works by retrieving similar cases of abnormal shadows expanding in a three-dimensional manner.
It automatically separates the complex interior of the organ into areas through image analysis and uses machine learning to recognise abnormal shadow candidates in each area.
By dividing up the organ spatially into periphery, core, top, bottom, left and right, and focusing on the spread of the abnormal shadows in each area, it becomes possible to view things in the same way doctors do when determining similarities for diagnosis.
In joint research with Professor Kazuo Awai of the Department of Diagnostic Radiology, Institute and Graduate School of Biomedical Sciences, Hiroshima University, this technology was tested using real-world data, and the result was an accuracy rate of 85% in the top five retrievals among correct answers predetermined by doctors.
Going forward, Fujitsu Laboratories will conduct numerous field trials using CT images for a variety of cases, while additionally aiming to contribute to the increased efficiency of medical care by deploying this technology with related solutions from Fujitsu Limited.
Original Article: Fujitsu develops AI technology for CT inspectionsNEXT ARTICLE
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