[Development Case] Introduction of Advanced Technology into Fundus Examination Devices

Acquisition of detailed biological tissue information and acceleration from examination to result presentation! Introduction of development cases.

The diagnosis of eye diseases is progressing daily, but the information from biological tissues is not necessarily sufficient, and there are limitations in understanding the pathological conditions. In this development, we are collaborating with inspection device manufacturers to obtain new tissue characteristic information, and we are using advanced technologies such as Deep Learning and GPGPU to maximize the use of that information, demonstrating means to understand pathological conditions from multiple perspectives and addressing this issue. In conventional methods, it took about one hour to compute data from a single examination, but we have successfully re-implemented this computation on GPGPU, reducing the time to approximately five minutes. [Development Example] ■ OS: Windows 10 ■ Development Period: 5 years ■ Number of Developers: 3 ■ Development Languages: Qt, C++, Python ■ Networks Used: DeepLabV2, V3 *For more details, please refer to the PDF document or feel free to contact us.

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