Statistical shape model based segmentation of medical images

被引：35

作者：

Neumann, A ^{[1
]}

Lorenz, C ^{[1
]}

机构：

[1] Univ Fed Armed Forces Hamburg, D-22039 Hamburg, Germany

来源：

COMPUTERIZED MEDICAL IMAGING AND GRAPHICS | 1998年 / 22卷 / 02期

关键词：

statistical shape description; landmarks; Fourier descriptors; wavelet descriptors; empirical covariances; principal component analysis; deformable models; boundary finding; biomedical image analysis;

D O I：

10.1016/S0895-6111(98)00015-9

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

This paper reviews several kinds of 2D shape representations by a set of parameters based on labeled points, Fourier descriptors and wavelet descriptors. Seven shape models for axial slices of spinal vertebra are derived by a statistical analysis of parameters corresponding to a set of example shapes and are subsequently compared. Two of the developed models are incorporated into methods for interactive segmentation of 2D gray level images. The first method is founded on Fourier descriptors, the second one is based on normalized sets of labeled points. Both methods are based on a model guided shape exploration. (C) 1998 Elsevier Science Ltd. All rights reserved.

引用

页码：133 / 143

页数：11

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