Image diagnosis assistance apparatus, data collection method, image diagnosis assistance method, and image diagnosis assistance program

Abstract

Provided are: an image diagnosis assistance apparatus capable of assisting diagnosis of an endoscopic image captured by an endoscopist; a data collection method; an image diagnosis assistance method;and an image diagnosis assistance program. The image diagnosis assistance apparatus is provided with a lesion assessment unit that assesses, by a convolutional neural network, the denomination and theposition of a lesion which is present in a digestive system endoscopic image of a patient captured by a digestive system endoscopic imaging device and information about accuracies thereof; and a display control unit that performs control for generating an analysis result image in which the denomination and the position of the lesion and the accuracies thereof are displayed and for displaying theimage on the digestive system endoscopic image. In the convolutional neural network, learning processing is performed on the basis of the denominations and the positions of the lesions that are present in a plurality of digestive system tumor endoscopic images predetermined by feature extraction of conditions of atrophy, intestinal metaplasia, swelling or depression of a mucous membrane, and mucous membrane color tone.

Description

technical field [0001] The invention relates to an image diagnosis auxiliary device, a data collection method, an image diagnosis auxiliary method and an image diagnosis auxiliary program. Background technique [0002] Cancer is the leading cause of death in the world. According to the World Health Organization (WHO), 8.8 million people died in 2015. According to internal organs, the digestive system including the stomach or large intestine accounts for the most. Stomach cancer, in particular, is the fifth most common malignant tumor and the third most common cause of cancer-related death in the world, with approximately 1 million new cases and approximately 700,000 deaths each year. The prognosis of gastric cancer patients depends on the stage (degree of progression) of the cancer at the time of diagnosis. Progressed gastric cancer has a poor prognosis, but the five-year survival rate of early gastric cancer is over 90%. Many gastric cancers can be cured by early detection...

AI Technical Summary

Problems solved by technology

However, the secondary inspection of endoscopic images takes a lot of time, so it becomes a heavy burden on the endoscopist at the medical site

[0005] Moreover, the diagnosis based on these endoscopic images can be said to be a subjective judgment based on experience and observation, and various false positive judgments and false negative judgments may occur.

In addition, medical equipment can perform to the greatest extent only when the two conditions of the performance of the equipment itself and the reliable operation of the operator are satisfied. However, in endoscopic diagnosis, sometimes the Reduced accuracy

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