The smart endoscopic medical display jointly developed by Champvision and Hitspectra Intelligent Technology win the 2020 National Innovation Award
The smart endoscopic medical display jointly developed by Champvision and Hitspectra Intelligent Technology integrates the technology of the Institute of Opto-Mechanics, Chung Cheng University and the clinical experience of the esophageal cancer team of the Department of Gastrointestinal Medicine, by using artificial intelligence and edge detection technology to detect esophageal tumors. Image and data are used for artificial intelligence earning and calculation, and artificial intelligence medical image identification system is developed, which can effectively combine AI artificial intelligence, hyperspectral image analysis and endoscopic image feature identification of esophageal tumors, and can identify the esophagus from endoscopic images The location of the tumor and the staging of histological cancelation at the same time, the accuracy rate can reach 85%. With this smart endoscopic medical system, there are opportunities to overcome many difficulties encountered by endoscopy in the diagnosis of esophageal cancer.
The development of this artificial intelligence medical imaging system will have the opportunity to reduce the time of patient endoscopy and the discomfort during examination, reduce the error of esophageal tumor slices, and improve the accuracy of early esophageal cancer diagnosis. If esophageal cancer can be diagnosed quickly and accurately, in addition to allowing patients to receive related treatments soon, it can also improve the prognosis and bring quality life to patients, thereby saving social medical resources. In the future, the development of this smart endoscopic medical display can store image data in the cloud to facilitate the integration of relevant medical record image data to assist future image data query and research. In addition to endoscopic diagnosis of esophageal cancer, it is hoped that this technology can be applied to medical imaging diagnosis of other different specialties in the future, in order to help different specialists solve the problem of clinical imaging diagnosis.
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