Neural fingerprint extraction and classification method and system

Abstract

The invention provides a neural fingerprint extraction and classification method. The method comprises an image acquisition step, a brain structure annotation step and a neural fingerprint extractionstep in sequence. The method has the advantages that information mining is performed on magnetic resonance images in different sequences, a unified fingerprint extraction and establishment method forall brain areas is formed through unified structure annotation establishment and positioning, a comprehensive neural fingerprint system is constructed, neural fingerprint standard libraries for different sexes and different ages are established, and therefore brain health assessment, disease classification and parting and disease prediction can be performed on a to-be-tested target; through the establishment of the neural fingerprint standard libraries, quantitative assessment and classification can be performed on brain development, brain senescence, neural diseases and mental diseases of a to-be-tested object, and talent assessment, advantage assessment, senescence assessment, rehabilitation assessment, assistant diagnosis, disease prediction and other technologies can be formed; and a standard technical foundation is laid for advantage cultivation, brain healthcare and diagnosis and prevention of brain diseases of human talents.

Description

technical field [0001] The invention relates to image processing technology and artificial intelligence recognition technology in the medical field, in particular to a neural fingerprint extraction and classification method and system. Background technique [0002] Magnetic resonance imaging is a commonly used medical tomographic imaging method, which uses magnetic resonance phenomena to obtain electromagnetic signals from the human body and reconstruct human body information. This technology uses the principle of nuclear magnetic resonance, according to the different attenuation of the released energy in different structural environments inside the material, and through the detection of the emitted electromagnetic waves by an external gradient magnetic field, the position and type of the atomic nucleus that constitutes the object can be known. This can be mapped into an image of the structure inside the object. Two-thirds of the weight of the human body is water, and the w...

AI Technical Summary

Problems solved by technology

[0003] The interpretation and classification of existing magnetic resonance brain images are completely dependent on the doctor's visual observation and subjective judgment based on experience. The discovery of lesions is overly dependent on experience and lacks quantifiable standards.

In addition, doctors are relatively subjective when writing film reading reports, lacking a unified quantitative standard and speech system, which creates a bottleneck for the standardization of electronic medical records and big data mining

Images