三维回归用于比较和绘制三维解剖结构。

Anatomy research international Pub Date : 2012-01-01 Epub Date: 2011-10-04 DOI:10.1155/2012/604543
Kendra K Schmid, David B Marx, Ashok Samal
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引用次数: 5

摘要

形状分析对各种学科都很有用,并且有许多应用。形状分析有许多方法,其中一种方法侧重于分析由物体上预定义的地标坐标表示的形状。本文讨论了三维回归,这是一种可以用于映射图像和形状的技术,这些图像和形状由一组三维地标坐标表示,用于比较和映射三维解剖结构。形状之间的相似程度可以使用三维决定系数(R(2))来量化。通过实验验证了该方法对同一人脸图像进行匹配的有效性。这些结果与仅使用两个维度时获得的R(2)值进行了比较,并表明使用三个维度可以提高正确匹配和区分面孔的能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Tridimensional Regression for Comparing and Mapping 3D Anatomical Structures.

Tridimensional Regression for Comparing and Mapping 3D Anatomical Structures.

Tridimensional Regression for Comparing and Mapping 3D Anatomical Structures.

Tridimensional Regression for Comparing and Mapping 3D Anatomical Structures.

Shape analysis is useful for a wide variety of disciplines and has many applications. There are many approaches to shape analysis, one of which focuses on the analysis of shapes that are represented by the coordinates of predefined landmarks on the object. This paper discusses Tridimensional Regression, a technique that can be used for mapping images and shapes that are represented by sets of three-dimensional landmark coordinates, for comparing and mapping 3D anatomical structures. The degree of similarity between shapes can be quantified using the tridimensional coefficient of determination (R(2)). An experiment was conducted to evaluate the effectiveness of this technique to correctly match the image of a face with another image of the same face. These results were compared to the R(2) values obtained when only two dimensions are used and show that using three dimensions increases the ability to correctly match and discriminate between faces.

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