APPARATUS AND METHOD FOR DIAGNOSING GASTRIC DISEASES ON BASIS OF ARTIFICIAL INTELLIGENCE DISCERNMENT MODEL AND THREE-DIMENSIONAL MODELING

An apparatus for diagnosing gastric diseases according to an embodiment may comprise: an image processing unit for obtaining a captured image of a stomach; a modeling unit for generating a three-dimensional model of the stomach on the basis of the image; an image analysis unit for discerning disease...

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Bibliographic Details
Main Authors HWANG, Sang Won, KIM, Hee Man
Format Patent
LanguageEnglish
French
Korean
Published 25.05.2023
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Summary:An apparatus for diagnosing gastric diseases according to an embodiment may comprise: an image processing unit for obtaining a captured image of a stomach; a modeling unit for generating a three-dimensional model of the stomach on the basis of the image; an image analysis unit for discerning disease information contained in the image by inputting the image to a machine learning-based discernment model that discerns gastric disease information; and a diagnosis unit for displaying the discerned disease information on the three-dimensional model. Dans un mode de réalisation, l'invention concerne un appareil permettant de diagnostiquer des maladies gastriques et pouvant comprendre : une unité de traitement d'image pour obtenir une image capturée de l'estomac ; une unité de modélisation pour générer un modèle tridimensionnel de l'estomac en fonction de l'image ; une unité d'analyse d'image pour discerner des informations de maladie contenues dans l'image par entrée de l'image dans un modèle de discernement basé sur l'apprentissage automatique et destiné à discerner des informations de maladie gastrique ; et une unité de diagnostic pour afficher les informations de maladie discernées par le modèle tridimensionnel. 일 실시예에 따른 위장 질환 진단 장치는 위장을 촬영한 영상을 획득하는 영상 처리부; 상기 영상을 기초로 상기 위장의 3차원 모델을 생성하는 모델링부; 위장의 질환 정보를 판별하는 머신러닝 기반의 판별 모델에 상기 영상을 입력하여 상기 영상에 포함된 질환 정보를 판별하는 영상 분석부; 및 상기 3차원 모델에 상기 판별된 질환 정보를 표시하는 진단부를 포함할 수 있다.
Bibliography:Application Number: WO2022KR16521