The invention discloses an
endoscope pneumoperitoneum pressure system based on AI
image evaluation and an intelligent adjusting method, and the method comprises the steps: 1, obtaining an original image of the
abdominal cavity of a patient through CT equipment, carrying out the
standardization processing of the original image, generating a standardized CT image
data set, and constructing a three-dimensional dynamic model of the
abdominal cavity of the patient based on an AI
algorithm; in the second stage, quantitative analysis of
subcutaneous fat thickness,
visceral organ volume and operable space volume is carried out on the three-dimensional dynamic model by adopting an AI segmentation
algorithm, and a personalized
pneumoperitoneum pressure target value Ptarget and an adjustment threshold range are generated through a
machine learning model in combination with basic illness state data of the patient; in the third stage, working data are collected in real time through a built-in sensor of the
endoscope system, and the working data are input into the
reinforcement learning model to dynamically calculate a pressure adjusting instruction
delta P; through deep fusion of the AI technology and
system closed-
loop control, the intelligent level of the
endoscope system is remarkably optimized, good hardware support is provided, and the function of optimizing the operation environment and effect is achieved.