LANDMARK-BASED METHODS FOR BIOMETRIC ANALYSES OF SHAPE

基于地标的形状生物特征分析方法

• 批准号: 2734550
• 负责人: FRED LEON BOOKSTEIN
• 金额: $ 11.85万
• 依托单位: UNIVERSITY OF MICHIGAN AT ANN ARBOR
• 依托单位国家: 美国
• 财政年份: 1986
• 资助国家: 美国
• 起止时间: 1986-08-01 至 1999-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/2734550
• 关键词: cardiovascular system; computer program /software; computer system design /evaluation; craniofacial; embryogenesis; human subject; image processing; morphology; neuroanatomy; skull; statistics /biometry

Morphometrics is the technology of measuring biological shape and shape change. Over the last decade, its two main traditions, the algebraic and the geometric, have merged in a synthesis that combines the full power of multivariate analysis with contemporary computer visualization tools for the detection and interpretation of patterns involving landmark points, locations that are arguably homologous on biological grounds across the forms of a data set. The present grant has been specifically responsible for many components of that synthesis; the thin-plate spline interpolant between landmark configurations, the basis of partial warps that its bending-energy matrix generates for linearized descriptions of shape variation, many algebraic and diagrammatic approaches to within-sample and between sample landmark patterns, and preliminary extensions of all these to the analysis of outlines and of whole medical images. In the 1990's these techniques have showed their value wherever the morphometrics of landmarks has been applied, from craniofacial surgery through neuroanatomical atlas design to evolutionary biology. Over the period of this competing continuation we will focus on combining the new morphometric techniques with existing tools of image analysis in diverse applications across a range of typical biomedical concerns. Aim 1 involves extending the algebraic formalisms developed earlier for landmarks to include alternate bases for shape space, other spline formulas, and other registration systems for detecting informative dimensions of image variability. Aim 2 extends recent breakthroughs in the fusion of outline or surface information with landmark information, including the representation of edge directions in-between landmarks and their incorporation into shape predictions. Aim 3 explores novel and very promising versions of the important "image registration problem": combination of landmark features with image features, "horizontal" with "vertical," to improve the accuracy of diagnoses and prognoses. The algebraic and geometric methods developed here may permit extension of many of these strategies toward the next frontier of morphometric data, processes of normal or diseased development in which landmark-based descriptions become more complex over time. All these Aims overlap with a fourth, a continual emphasis upon visualization, simplification, exemplification, and dissemination to the growing community of consumers of this new morphometrics. Demonstration data sets will be drawn from cranio- facial surgery, cardiology, and neuroanatomy. The new techniques are intended to become crucial software tools for routine scientific exploitation of clinical medical images. Diverse image-based empirical studies will thereby continue to gain both in statistical efficiency and int eh effectiveness with which information is extracted for clinical and comparative purposes.

形态计量学是测量生物形状和形状的技术 改变。 在过去的十年中，它的两个主要传统，即代数和 几何形状已合成，结合了全部功能 使用现代计算机可视化工具的多元分析 检测和解释涉及地标点的模式， 可以说是在整个生物学基础上是同源的 数据集的形式。 目前的赠款是特别责任的 对于该综合的许多组成部分；薄板样条插值 在具有里程碑意义的配置之间，部分扭曲的基础是 弯曲能量矩阵生成用于形状的线性描述 变异，许多代数和图解方法，用于样本内和 在样本地标模式和所有这些的初步扩展之间 分析大纲和整个医学图像。 在1990年代 这些技术在形态计量学的任何地方都显示出它们的价值 从颅面手术到 神经解剖图集设计至进化生物学。 在这个竞争继续的时期，我们将专注于结合 现有图像分析工具的新形态计量技术 在一系列典型的生物医学问题上的各种应用。 目标1 涉及扩展较早为地标开发的代数形式主义 包括形状空间，其他样条公式和 用于检测图像信息维度的其他注册系统 可变性。 AIM 2扩大了概述融合的最新突破 或具有里程碑意义的信息的表面信息，包括 地标之间的边缘方向的表示 纳入形状预测。 AIM 3探索小说，非常 重要的“图像注册问题”的有希望的版本： 地标特征与图像特征的组合，“水平”与 “垂直”，以提高诊断和预后的准确性。 这 此处开发的代数和几何方法可能允许扩展许多 这些策略在下一个形态计量数据的前沿 正常或患病发展的过程中基于里程碑的过程 随着时间的流逝，描述变得更加复杂。 所有这些目标与 第四，不断强调可视化，简化， 示例和传播给不断增长的消费者社区 这种新的形态计量学。 演示数据集将从Cranio-绘制 面部手术，心脏病学和神经解剖学。 新技术是 打算成为常规科学的关键软件工具 对临床医学图像的开发。 基于图像的多样化经验 因此，研究将继续提高统计效率和 提取临床和提取信息的int EH有效性 比较目的。