Part category identification method and inspection quality monitoring system
A recognition method and category technology, which is applied in the field of inspection quality monitoring and image recognition technology, and can solve problems such as missed diagnosis of diseases
Pending Publication Date: 2022-01-11
紫东信息科技(苏州)有限公司
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However, since the upper gastrointestinal tract involves many parts, for example: the upper gastrointestinal tract includes the oropharynx, the esophagus, the cardia, the cardia, the anterior wall of the gastric fundus A, and the posterior gastric fundus P There are dozens of parts such as the gastroscope, and the gastroscopy doctor is likely to miss some parts when operating the gastroscope, resulting in missed diagnosis of diseases in these parts
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[0043] The present disclosure will be further described in detail below with reference to the drawings and embodiments. It can be understood that the specific implementation manners described here are only used to explain relevant content, rather than to limit the present disclosure. It should also be noted that, for ease of description, only parts related to the present disclosure are shown in the drawings.
[0044] It should be noted that, in the case of no conflict, the implementation modes and the features in the implementation modes in the present disclosure can be combined with each other. The technical solutions of the present disclosure will be described in detail below with reference to the accompanying drawings and in combination with implementation manners.
[0045] figure 1 is a schematic flow chart of a part category recognition method according to an embodiment of the present disclosure.
[0046] refer to figure 1 , the part category recognition method S100, ...
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The invention provides a part category identification method, which comprises: carrying out vectorization representation on a plurality of target images to obtain an image representation vector of each target image, wherein the plurality of target images are continuous frame images; performing feature extraction on the image representation vector of each target image to obtain a feature representation vector with a first preset dimension of each target image; performing dimension compression on the feature representation vector with the first preset dimension of each target image to obtain an image compression intermediate representation vector with a second preset dimension of each target image; obtaining a final image feature of each target image based on the image compression intermediate representation vector with the second preset dimension of each target image; and generating a predicted value of each part category of each target image based on the final image features of all the target images and a pre-acquired dependency relationship among the part categories. The invention further provides an inspection quality monitoring system based on part category recognition.
Description
technical field [0001] The present disclosure relates to the field of image recognition technology and the field of inspection quality monitoring technology, and in particular to a method for part category recognition and a system for inspection quality monitoring based on part category recognition. Background technique [0002] According to the global cancer statistics, 4 of the top 10 tumors come from the digestive tract. Gastrointestinal diseases, including benign, precancerous and malignant diseases of the digestive tract, are seriously threatening the quality of life and life safety of patients, causing a huge health burden. The incidence of digestive tract tumors ranks first among all kinds of malignant tumors in my country. Due to the remarkable effect of gastrointestinal endoscopy in the diagnosis of gastrointestinal cancer, it has been recommended as the main diagnostic method for gastrointestinal cancer. Specifically, the gastrointestinal endoscope can directly d...
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Login to View More IPC IPC(8): G06V10/764G06V10/82G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06N3/047G06F18/2415
Inventor 戴捷
Owner 紫东信息科技(苏州)有限公司