Cholelithiasis intelligent diagnosis APP based on deep learning

Abstract

The invention relates to a cholelithiasis intelligent diagnosis APP based on deep learning, wherein the APP relates to the fields of image processing, medical treatment big data and deep learning. Theoperation method of the cholelithiasis intelligent diagnosis APP comprises the following steps of 1), performing data acquisition through a CT scanner, and obtaining a cholelithiasis CT medical image; 2), performing preprocessing of the cholelithiasis CT medical image by a data transmission and analysis unit; 3), according to the preprocessed data, through an intelligent auxiliary diagnosis unit,marking the image by means of an image marking algorithm based on a deep convolutional neural network, performing automatic characteristic extraction and identification on the marked image data by the convolutional neural network after dimension reduction, and analyzing a condition; 4), performing feedback of a diagnosis result to a patient in an electronic medical report, and transmitting a diagnosis record to cloud server for storage and setting a file, thereby supplying to a related constitute and an assigned hospital as a clinical reference; and 5), expanding the data set by the image data after definite diagnosis by a doctor, performing parameter optimization on the model, and improving diagnosis accuracy of the cholelithiasis.

Description

technical field [0001] The invention relates to the technical field of cholelithiasis diagnosis equipment, in particular to an intelligent diagnosis APP for cholelithiasis based on deep learning. Background technique [0002] Cholelithiasis is a common digestive system disease. There are many kinds of diseases, and the pathogenic factors are complicated. It has the characteristics of high incidence rate and difficulty in dissolving stones. In addition, there are various types and forms of cholelithiasis, and the lesion forms of some cholelithiasis are also very similar, which greatly hinders the correct diagnosis and treatment of cholelithiasis. Under such circumstances, some young hepatobiliary physicians need to study for a long time before they can master the skills of diagnosing gallstone disease proficiently, which brings great challenges to the clinical diagnosis of hepatobiliary physicians. For patients, gallstone disease cannot be consulted on the Internet according...

AI Technical Summary

Problems solved by technology

According to the survey, most of the deep learning models currently on the market cannot complete the above tasks.

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