TISSUE SCATTERER ANALYSIS WITH SPECTRAL REDUNCANCY

具有光谱冗余的组织散射体分析

• 批准号: 6327606
• 负责人: KEVIN D DONOHUE
• 金额: $ 26.78万
• 依托单位: DREXEL UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2000
• 资助国家: 美国
• 起止时间: 2000-07-03 至 2001-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6327606
• 关键词: bioimaging /biomedical imaging; breast neoplasm /cancer diagnosis; breast neoplasms; computer assisted diagnosis; computer simulation; early diagnosis; human data; image processing; liver neoplasms; mathematical model; method development; neoplasm /cancer diagnosis; noninvasive diagnosis; statistics /biometry; ultrasonography

The continuation of this research project aims at extracting new and relevant tissue information from spectra of broadband ultrasonic echoes. The ultimate goal of this project is to improve the detection capabilities of malignant tissues with ultrasound imaging. A unique aspect of this project is its focus on characterizing Fourier phase and magnitude of rf ultrasonic tissue echoes with spectral redundancy methods, such as those based on the spectral autocorrelation function (also referred to as the generalized spectrum). Previous work has shown that estimates using the generalized spectrum can reliably reveal the nature of tissue regularity in the presence of diffuse scatterers over relatively small (several millimeters) segments of tissue. The good convergence properties of spectral correlation methods have allowed for creating relatively high resolution parametric images that reveal spatial changes in tissue structure parameters, such as the mean scatterer spacing and echo specularity. Future work focuses on understanding and applying new generalized spectrum features such as the specular scatterer size, dispersion, multiple scatterer spacings, and the degree of regularity for both resolvable and unresolvable spacings. While other methods have been used to extract resolvable scatterer spacing information, the new features utilize the unique way in which the generalized spectrum presents information as a function of frequency. In addition, statistical tests and significance levels will be used in analyzing generalized spectra for more automatic and repeatable classifications of tissue regions. B-scans on liver and breast tissues will be examined to determine changes in spectral redundancy parameters for normal, benign and malignant tissue regions. Databases will be established to statistically examine the nature and consistency with which malignant neoplasms disrupt the normal tissue structures. The success of the proposed research will enhance capabilities for diagnostic ultrasound, particularly for early detection of cancer.

该研究项目的继续旨在提取新的和 来自宽带超声回波频谱的相关组织信息。 该项目的最终目标是提高检测能力 恶性组织的超声成像。这其中一个独特的方面 该项目的重点是表征射频的傅里叶相位和幅度 采用频谱冗余方法的超声组织回波，例如 基于谱自相关函数（也称为 广义谱）。先前的工作表明，使用估计 广义谱可以可靠地揭示组织规律性的本质 在相对较小（几个 毫米）的组织片段。良好的收敛特性 谱相关方法允许创建相对较高的 揭示组织空间变化的分辨率参数图像 结构参数，例如平均散射体间距和回波 镜面反射度。 未来的工作重点是理解和应用新的广义频谱 诸如镜面散射体尺寸、色散、倍数等特征 散射体间距，以及可分辨和可分辨的规律性程度 无法解析的间距。虽然已使用其他方法提取 可解析的散射体间距信息，新功能利用 广义谱将信息呈现为一种独特的方式 频率的函数。此外，统计检验和显着性 水平将用于分析广义光谱以实现更自动化 和组织区域的可重复分类。 将检查肝脏和乳腺组织的 B 扫描以确定变化 正常、良性和恶性组织的光谱冗余参数 地区。将建立数据库以统计检查性质 以及恶性肿瘤破坏正常组织的一致性 结构。拟议研究的成功将增强能力 用于诊断超声，特别是用于癌症的早期检测。