The Research Of Tissue Elastography Algorithm Based On Ultrasound

The mechanical properties of biological soft tissue are always dependent on the tissue’sphysical composition form and biological activity, including biological tissue elasticity hasgreat reference value for the diagnosis of many diseases. However, the traditional mode ofmedical imaging such as ultrasound imaging (U.S.), magnetic resonance imaging (MRI),X-ray imaging, computed tomography scan(CT) can not provide the basic mechanicalproperties of tissue elasticity directly. Ultrasound elasticity imaging (elastography) hasdeveloped rapidly in recent years and has applied in medicine diagnosis, biological tissueelastic parameters obtained through this technology can provide critical evidence for anumber of important clinical diagnosis of the disease.Ultrasonic transient elastography, the main object of study in this paper, canautomatically grade liver fibrosis assessment by measuring human liver’s elastic modulus, andhere we implement an ultrasound transient elastography system. Taking into account that theultrasound elasticity imaging algorithm is a data processing of high-density computation, toreduce the computational complexity of the algorithm and cut down the whole running timeof system, will be very meaningful if real-time or quasi real-time imaging is required. Basedon the research of the traditional exhaustive search match algorithm, combining with theactual imaging target and in-depth mining the characteristics of the elasticity imagingalgorithm, this paper describes a fast matching algorithm, this approach is based on a priorquality estimation and suitable for detection of liver fibrosis. This method has a fullconsideration about the physical relevance of the results before and after the match operations,it assumes that a continuous displacement field is always exist, and reduce the amount ofcross-correlation matching operation by effective use of prior results, the results ofelastography using new method has verify the algorithm the feasibility and effectiveness inthis paper where the test data come from volunteers liver experiments.In addition, during Ultrasound elastography data acquisition, the test data wouldinevitably come with a series of noise, some of noise is in part from the complex environmentof biological tissues. Aim to this particular case, this paper propose a new method whichbased on the energy threshold adaptive empirical mode decomposition algorithm for the pretreatment of the echo signal data, this method analysis signal from the perspective ofefficient energy distribution, and an adaptive imaging system filter module is finished whichespecially suitable for the imaging system of multi-probe mode with a good device scalability.Finally, the work has done in this paper is summarized and based on this also discussfurther research ideas.