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首页> 外国专利> METHOD OF ASSISTING DISEASE DIAGNOSIS BASED ON ENDOSCOPE IMAGE OF DIGESTIVE ORGAN, DIAGNOSIS ASSISTANCE SYSTEM, DIAGNOSIS ASSISTANCE PROGRAM, AND COMPUTER-READABLE RECORDING MEDIUM HAVING SAID DIAGNOSIS ASSISTANCE PROGRAM STORED THEREON

METHOD OF ASSISTING DISEASE DIAGNOSIS BASED ON ENDOSCOPE IMAGE OF DIGESTIVE ORGAN, DIAGNOSIS ASSISTANCE SYSTEM, DIAGNOSIS ASSISTANCE PROGRAM, AND COMPUTER-READABLE RECORDING MEDIUM HAVING SAID DIAGNOSIS ASSISTANCE PROGRAM STORED THEREON

机译：基于消化器官的内窥镜图像，诊断辅助系统，诊断辅助计划和计算机可读记录介质的辅助疾病诊断方法，所述诊断辅助程序存储在其上

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摘要

A diagnostic assistance method for a disease based on an endoscopic image of a digestive organ with use of a convolutional neural network (CNN), and the like are provided. A diagnostic assistance method for a disease based on an endoscopic image of a digestive organ with a CNN according to a first embodiment trains the CNN using a first endoscopic image of the digestive organ and at least one final diagnosis result on positivity or negativity to the disease in the digestive organ, a past disease, a severity level, and information corresponding to a site where an image is captured, the final diagnosis result being corresponding to the first endoscopic image, and the trained CNN outputs at least one of a probability of the positivity and/or the negativity to the disease in the digestive organ, a probability of the past disease, a severity level of the disease, an invasion depth of the disease (infiltration depth), and a probability corresponding to the site where the image is captured, based on a second endoscopic image of the digestive organ.
机译：提供了一种基于使用卷积神经网络（CNN）的消化器官的内窥镜图像的诊断辅助方法。基于第一实施方式的CNN的消化器官的内窥镜图像的诊断辅助方法使用消化器官的第一内窥镜图像列举CNN，并且至少一个最终诊断导致对疾病的积极性或消极性在消化器官，过去疾病，严重性等级和对应于捕获图像的站点的信息中，对应于第一内窥镜图像的最终诊断结果，并且训练的CNN输出至少一个概率阳性和/或对消化器官疾病的消极性，过去疾病的概率，疾病的严重程度，疾病的侵袭深度（渗透深度），以及对应于图像的网站的概率基于消化器官的第二内窥镜图像捕获。

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