Benefits of Three Dimensional Data in Characterizing Images

本研究项目是关于超声组织的 特征化（UTC），这是一种自动化的检测手段， 使用超声图像对患病组织进行分类。 电流 这一领域的研究是基于计算机对两个- 三维（2-D）超声图像。 该项目将扩展当前的 二维到三维图像。 使用3-D图像允许表征组织纹理沿着 任何平面或使用任何体积。 平面将由矢量或 3D图像中的某个边界，即，肾脏和 壁和肝壁。 现有的二维算法将被改造 到3D格式。 设计任何二维算法的一般映射是 复杂，但幸运的是，所涉及的特定参数 自己对这种转变。 最终的目标是向人类呈现一个三维彩色编码图像 用于解释、操作和诊断的操作员。 这 机器计算和人类智能的结合， 提高了准确性，并有可能发现新的 技术.

This research project is concerned with ultrasonic tissue characterization (UTC) which is an automated means of detecting and classifying diseased tissue using an ultrasound image. Current research in this area is based upon computer manipulation of two- dimensional (2-D) ultrasound images. This project will extend current 2-D to 3-D images. Use of 3-D images permits the characterization of tissue texture along any plane or using any volume. Plane will be defined by vectors or by some boundary in the 3-D image, i.e., the boundary between the kidney wall and the liver wall. Existing 2-D algorithms will be transformed to the 3-D format. Devising a general mapping of any 2-D algorithm is complex, but fortunately the particular parameters involved lend themselves to this transformation. The ultimate goal is to present a 3-D color-coded image to a human operator for interpretation, manipulation and diagnosis. This combination of machine computation and human intelligence leads to increased accuracy and has the potential of discovering new techniques.