Optical coherence tomography based three-dimensional blood flow imaging method based on feature space

Abstract

The invention discloses a three-dimensional blood flow imaging method and system based on optical coherence tomography of feature space. The OCT scattering signal of the scattering signal sample in the three-dimensional space is collected by the collector; the two-dimensional feature space is constructed through the theoretically established classifier combined with the local signal-to-noise ratio and decorrelation coefficient of the OCT scattering signal, and the classification of the dynamic blood flow signal and the static tissue is realized. , which specifically includes: using the first-order and zero-order autocovariance to calculate and analyze the OCT scattering signal, and obtain the two characteristics of the signal-to-noise ratio and decorrelation of each OCT scattering signal; constructing a two-dimensional feature space of the reciprocal of the signal-to-noise ratio-decorrelation coefficient ; Based on multivariate time series theory, construct a linear classifier for ID space and remove static surrounding tissue background. The invention can significantly suppress the influence of system noise on blood flow imaging, improve the contrast of blood flow images, especially the visibility of blood vessels in deep tissues, and improve the accuracy of blood flow quantification.

Description

technical field [0001] The present invention generally relates to the field of biomedical imaging, and more specifically relates to optical coherence tomography (Optical Coherence Tomography, OCT) and optical coherence tomography (OCT Angiography, OCTA) associated blood flow imaging methods and Blood flow classification method based on time series model. Background technique [0002] Blood flow is an important indicator to measure physiological function and pathological state. Currently, the commonly used angiographic technique in clinical practice requires intravenous injection of exogenous markers, and the possible side effects make it unsuitable for long-term and frequent tracking of human blood flow. Detect and the physical condition of some patients. In recent years, OCTA, an angiographic technique developed on the basis of optical coherence tomography, replaces traditional exogenous fluorescent markers with endogenous blood flow movement. The ability to perform clear...

AI Technical Summary

Problems solved by technology

However, simple intensity masks lead to high classification error rates and low motion contrast due to complex dependencies between decorrelation coefficients and signal intensity

[0005] Most of the existing OCTA classification methods lack strong theoretical support, and are interfered by the difference between the template parameters and the actual biological tissue, and cannot clearly distinguish the accurate classification of dynamic and static signals; or use complex estimators to modify the signal-to-noise ratio to decorrelate The influence of the calculation is complex and the background noise caused by the static area cannot be removed

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