An Elastic Imaging Method Based on Empirical Manifold

Abstract

The invention discloses an elastic imaging method based on empirical manifolds, which includes the following steps: 1) Segment the RF signal collected after compressing the tissue, and determine the segment length and segment spacing according to the requirements of resolution and smoothness; 2) Select a segment of the pre-compression signal, determine the search range and search step size of the corresponding p post-compression signals, and use linear interpolation to obtain the post-compression segmental signal; 3) Calculate a layer of post-compression signals using the residual complexity RC The complexity between the windows, and then use it to calculate the similarity between the signal layer and the layer after compression, and use the similarity as the boundary weight of the graph; 4) Find the shortest length of each window in the pre-compression tissue and post-compression search range Path; 5) Output the displacement estimation map, and use the least squares method to fit the curve to obtain the strain estimate, and then combine the distribution conditions to reconstruct the tissue elasticity map. The method can further improve the accuracy of the displacement estimation algorithm in quasi-static elastography, thereby improving the quality of the finally obtained elastogram.

Description

technical field [0001] The invention relates to the field of medical elastic imaging, in particular to an elastic imaging method based on empirical manifolds. Background technique [0002] Elastography is a non-invasive method that uses soft tissue stiffness or strain images to detect or classify tumors. Elastography has been applied to several imaging modalities, such as ultrasound, magnetic resonance elastography (MRE), and computed tomography, showing great utility in medical applications. Elasticity imaging is to convert the acquired elastic information of biological materials into visible light images that doctors are accustomed to, so that doctors can judge the material mechanical properties of tissues through visible light images, and then judge the possible pathology of corresponding tissues or organs according to the soft and hard conditions of tissues. change as well as its position, shape and size. [0003] Since the quasi-static elastography technology was prop...

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Problems solved by technology

[0006] By analyzing the existing quasi-static medical ultrasound elastography technology, we found that the technology field is still facing many challenges, such as: significant error points caused by incorrect matching windows, real-time problems of elastography, etc.

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