Lin-Yuan Kao, Medical Technician, Dept. of Pathology
In 2020, NCKU Hospital implemented a digital pathological diagnosis and application system that continues to be used. Conventional pathological tissues are sliced and scanned to create a real-time cloud pathological image database. A digital smart-AI pathological analysis and calculation platform for big data was developed to assist pathologists with diagnosing patients efficiently, which allows for a new generation of smart medical care that meets international standards.
The NCKU Hospital digital pathological diagnosis and application system is used for the following purposes:
1.Cancer-tissue slice-scan image informatization, which provides real-time online image reading throughout the year.
2.Information integration with the in-hospital reporting system; digital pathological images are linked for reading when reports are edited.
3.Provision of digital pathological case images for exchanges and discussions during interdisciplinary care meetings.
4.Wired or wireless transmission of digital pathological images for reading on mobile devices, laptops, and workstations.
5.Provision of a maximum of nine digital pathological image files for synchronous positioning when reading and labeling to enable simultaneous viewing of different straining results of the same lesion, which can optimize diagnoses.
6.Development of an AI calculation and analysis software platform in collaboration with the NCKU Department of Computer Science and Information Engineering, which has been used to treat specific types of cancer.
7. Construction of user interfaces for external servers for the following purposes:
(1)Real-time interhospital and international discussions on the digital pathological images of difficult medical cases.
(2)Digital pathological education in the NCKU College of Medicine.
(3)Case exchanges and discussions in meetings outside NCKU Hospital.
Developing a smart-AI pathological diagnosis and application system is an urgent mission for NCKU Hospital. Such a system can improve the quality of our health-care institution and our patient care.
Figure 1. Real-time reading of digital pathological images through web-based applications such as Chrome.
Figure 2. Highlighting the tumor sites of live cancer through AI calculations.
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