A Method of Ultrasonic CT Imaging Based on Spatial Coherence

Abstract

The invention discloses an ultrasonic CT imaging method based on space coherence. The method includes the following steps of firstly, collecting data to obtain original echo data; secondly, preprocessing the data; thirdly, meshing an imaging area; fourthly, conducting DMAS calculation treatment based on the space coherence for each meshed imaging point to obtain initial imaging signals of the meshed imaging points; fifthly, conducting data postprocessing to finally obtain an ultrasonic CT image. On the basis of the formation characteristics of virtual receiving signals in a filtering delay multiplication and superposition algorithm, by calculating the space coherence of any two signals of the virtual receiving signals in the filtering delay multiplication and superposition algorithm and weighting the virtual received signals, compared with the prior art, the problems of a zero-phase filtering delay multiplication and superposition algorithm applied in the ultrasonic CT reflection imaging field can be effectively solved, and a high-contrast high-noise-ratio and low-sidelobe-level ultrasonic CT image can be reestablished.

Description

technical field [0001] The invention belongs to the technical field of ultrasonic tomography, and more particularly relates to an ultrasonic CT imaging method based on spatial coherence. Background technique [0002] Ultrasound CT imaging, that is, ultrasonic tomography, has the advantages of high resolution, 360° omnidirectional scanning, no extrusion, no radiation, and low cost. It has important clinical value and application prospects in breast cancer screening and early diagnosis. [0003] Ultrasound CT imaging methods include reflection imaging, sound velocity imaging and attenuation imaging. Reflection imaging depicts the anatomical structure of the target, and sound velocity and attenuation imaging shows the functional changes of the target. The three complement each other and are indispensable. [0004] The Computed ultrasound risk evaluation system (Computed ultrasound risk evaluation, CURE) developed by the Karmanos Cancer Center in the United States can reconstru...

AI Technical Summary

Problems solved by technology

The CURE system uses the Delay and sum algorithm, but the image reconstructed by this method still needs to be improved in terms of contrast and noise suppression

The Zero-phase filtered delay multiply and sum (ZPF-DMAS) delay multiply and sum algorithm has been introduced into the field of ultrasound CT in recent years. Although this method can suppress sidelobes and noise to a certain extent, it is still found that this method reconstructs images There are still the following problems: (1) the side lobe level and contrast still need to be improved; (2) the background is not uniform, and the contrast to noise ratio (CNR) is low

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