Hilbert transform-fundamental frequency estimation based method for estimating mean trabecular bone spacing

Abstract

The invention belongs to the technical field of medical ultrasound, in particular to a Hilbert transform-fundamental frequency estimation based method for estimating mean trabecular bone spacing. The method comprises the following steps: first, extracting enveloping of an ultrasonic backscattered signal after analog-to-digital conversion by adopting Hilbert transform, and performing down sampling on the enveloped signal; and then, processing the enveloped signal respectively by two fundamental frequency estimation algorithms, namely instantaneous fundamental frequency estimation (EB) and Yin (YIN) based on events, finding out the fundamental frequency of the enveloped signal from a last decision module, and reckoning the mean trabecular bone spacing by the fundamental frequency and known ultrasound transmission speed. The method raises to utilize the method of Hilbert transform-fundamental frequency estimation to study the mean trabecular bone spacing for the first time, and has stronger robustness on changes of white noise, random scatter echo and regular scatter echo, and more accurate estimation on different mean trabecular bone spacing compared with the traditional method for directly estimating the mean trabecular bone spacing.

Description

technical field [0001] The invention belongs to the technical field of medical ultrasound, in particular to a method for estimating the average trabecular distance of cancellous bone. Background technique [0002] With the aggravation of population aging, osteoporosis has become a serious social problem. It will cause the degradation of bone microstructure, thereby reducing bone strength and increasing the chance of fracture. At present, more than 200 million people in the world suffer from osteoporosis, and 20-30% of women suffer from osteoporosis to varying degrees. Currently the most commonly used diagnostic method is dual-energy X-ray (DXA) measurement of bone mineral density (BMD), but it cannot characterize bone microstructure; on the other hand, DXA has the disadvantages of radioactivity and high cost. [0003] Because ultrasound can reflect the microstructure information of bone, the method of using ultrasound to diagnose osteoporosis has attracted the attention of ...

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Problems solved by technology

[0005] These algorithms have better estimation performance when the experimental signal has a high signal-to-noise ratio and the random scattering amplitude is small, but in the case of a low signal-to-noise ratio and a large random scattering amplitude, there are more or less estimation errors Too large, the estimated variance is relatively large, etc.

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