Fujitsu has announced the development of an AI-based technology that will retrieve similar disease cases from a computed tomography (CT) database of previously taken images. It has been developed with joint efforts of Fujitsu Laboratories and Fujitsu R&D Center Co. Ltd. It will work by retrieving similar cases of abnormal shadows expanding in a 3-dimensional manner.
There are existing technologies used by doctors to specify an area of focus in a certain slice image and retrieve other patients with similar slice images. Such techniques have proved to be beneficial when the abnormal shadows are concentrated at one place, like an early-stage lung cancer.
However, in diffuse lung diseases, abnormal shadows are spread throughout the organ in all directions which make it mandatory for the doctors to re-confirm 3-dimensional similarities and hence it takes a great deal of time.
Fujitsu Develops AI-Based Technology to Retrieve Similar Cases (Image Courtesy: Fujitsu)
So, in order to resolve the issue, Fujitsu has developed this AI-based technology that accurately retrieves similar cases in which abnormal shadows have spread in 3 dimensions. It automatically separates the complex interior of the organs into areas through image analysis, with machine learning to recognize abnormal shadow candidates in each area.
By dividing up the organ spatially into periphery, core, top, bottom, left, and right, one can focus on the spread of abnormal shadows in each area. This facilitates doctors to view things in the same way as determining similarities for diagnosis.
The technology was tested using real-world data resulting in 85% accuracy in the top 5 retrievals among correct answers pre-determined by the doctors. This technology is expected to lead to an increased efficiency in diagnostic tasks for doctors. It also reduces the time needed to identify the correct diagnosis for cases where identification previously took a lot of time.
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