Fujitsu Develops AI-Based Technology to Retrieve Similar Disease Cases in CT Inspections

June 26, 2017 — Fujitsu Laboratories Ltd. announced development of 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. Ltd., works by retrieving similar cases of abnormal shadows expanding in a three-dimensional manner.

Technologies already exist to retrieve similar cases based on CT images for such diseases as early-stage lung cancer, in which abnormal shadows are concentrated in one place. For diffuse lung diseases like pneumonia, however, in which abnormal shadows are spread throughout the organ in all directions, it has been necessary for doctors to reconfirm three-dimensional similarities, increasing the time needed to reach a conclusion.

Now Fujitsu Laboratories has developed an artificial intelligence (AI)-based technology that can accurately retrieve similar cases in which abnormal shadows have spread in three dimensions. The technology automatically separates the complex interior of the organ into areas through image analysis, and uses machine learning to recognize 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 Prof. 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 percent in the top five retrievals among correct answers predetermined by doctors. This technology is expected to lead to increased efficiency in diagnostic tasks for doctors, and could reduce the time required to identify the correct diagnosis for cases in which identification previously took a great deal of time.

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.

“The fact that we have been able to demonstrate the possibility of retrieving CT images where abnormal shadows have similar natures and three-dimensional distribution has important medical implications. Moving forward, this technology has the potential to provide doctors with clinically useful information by retrieving similar CT images from cases that were difficult to diagnose and treat, and we can anticipate that this will improve the accuracy and efficiency of medical care. By grouping morphologically similar images, and investigating whether there are any common genetic abnormalities within these groups, the technology may present new ways of thinking about diseases and offers the possibility of numerous clinical applications. It's a technology that we have great expectations for in the future,” said Awai.

Details of this technology will be announced at the Pattern Recognition and Media Understanding (PRMU) conference to be held by the Institute of Electronics, Information and Communication Engineers at Tohoku University (Sendai, Miyagi prefecture) on June 22-23.

For more information: www.fujitsu.com