Disease auxiliary diagnosis method based on image identification

Abstract

The embodiment of the invention relates to the field of computers and discloses a disease auxiliary diagnosis method based on image identification. The method comprises the steps of receiving an uploaded symptom image of a to-be-diagnosed patient; extracting to-be-diagnosed characteristics of the symptom image of the to-be-diagnosed patient by use of a deep learning algorithm; establishing a to-be-diagnosed characteristics set; comparing the to-be-diagnosed characteristics set with a standard characteristics set of a standard symptom image of each disease in a training gallery to acquire an image similarity between the symptom image of the to-be-diagnosed patient and the standard symptom image of each disease, and determining the probability of the to-be-diagnosed patient who suffers from each disease according to the image similarity. Through the above-mentioned mode, the embodiment can rapidly associate the to-be-diagnosed patient with one or more diseases and saves a lot of time for further definite diagnosis.

Description

technical field [0001] The embodiments of the present invention relate to the field of computers, in particular to a method for aided disease diagnosis based on image recognition. Background technique [0002] Rare diseases are also called orphan diseases. The World Health Organization defines diseases or lesions that affect 0.065% to 0.1% of the population as rare diseases. The vast majority of rare diseases are congenital, and the course of the disease develops slowly. Its prevalence rate is low, but patients are often life-threatening. [0003] At present, the way to diagnose rare diseases is to establish disease research and treatment centers. Such institutions have obvious regional characteristics, and patients’ conditions cannot be diagnosed in time. For most doctors, due to the lack of rare disease diagnosis and Treatment experience greatly prolongs the time required for diagnosis. Doctors mainly diagnose the type of rare disease based on the patient's clinical mani...

AI Technical Summary

Problems solved by technology

The vast majority of rare diseases are congenital, and the course of the disease develops slowly. Its prevalence rate is low, but patients are often life-threatening

[0003] At present, the way to diagnose rare diseases is to establish disease research and treatment centers. Such institutions have obvious regional characteristics, and patients’ conditions cannot be diagnosed in time. For most doctors, due to the lack of rare disease diagnosis and Treatment experience, greatly prolonging the time required for diagnosis

Doctors mainly diagnose the type of rare disease based on the patient's clinical manifestations, but the clinical manifestations gradually worsen with the development of the disease, which makes the diagnosis of rare diseases a difficult problem for doctors and patients. Rare patients The average time from onset to accurate diagnosis is about 4.8 years. Failure to diagnose in time affects the quality of life of countless rare disease patients

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