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ULTRASOUND ECHO SIGNAL ANALYSIS AND TISSUE HISTOLOGY

ULTRASOUND ECHO SIGNAL ANALYSIS AND TISSUE HISTOLOGY
超声回波信号分析和组织组织学
批准号:
2009859
负责人:
NAVALGUND A RAO
金额:
$10.45万
依托单位国家:
美国
项目类别:
财政年份:
1996
资助国家:
美国
项目状态:
已结题
起止时间:
1996-09-20 至 1999-08-31

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中文摘要
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英文摘要
DESCRIPTION (Adapted from Applicant's Abstract): Statistical moments of ultrasound echoes from a medium such as soft tissue carry some information about the underlying random scattering microstructure of the tissue. These moments also depend on instrument dependent factors, however, such as the system resolution cell volume (axial and lateral resolution). The first task, therefore, is to remove this influence. To achieve this objective, and to extract more quantitative information about the tissue microstructure under investigation, a multibandwidth, multispectral pulse probing technique is proposed. The variation of the 2nd normalized moment of the echo signal intensity is examined as a function of cell volume and spectral content of the probed pulse. Independent cell volume measurements provide the basis for extracting robust features such as intercept and straight line slope on 2nd normalized moment verses inverse of cell volume plots. These two features are shown to be useful in differentiating between three different sponge structures (pore size varying form 2 mm to 0.5 mm). A rationale is presented that soft tissue, particularly liver tissue, has a scattering microstructure similar to the sponge structure studied. Therefore, a major objective is to apply this technique to excised liver and breast tissue samples. Histologic sections are considered the gold standard for tissue pathology. Therefore, the second major objective is to build a "bridge of understanding" between tissue histology and the quantitative analysis of the echo signal. A mathematical tissue modeling and simulation procedure has been developed using the microstructure of the tissue under study as input. This information is obtained from histologic sections. Moments of the simulated echo signal will be analyzed and compared to experimental results on real tissue. The model can be updated in an iterative fashion until some reasonable level of agreement is achieved. Finally, a third major objective is to determine whether the proposed methods have enough sensitivity to distinguish between "normal" and pathological tissue.
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