Three-dimensional segmentation of CT images using neural network

被引：0

作者：

Bao, XD ^{[1
]}

Xiao, SJ ^{[1
]}

Xu, ZQ ^{[1
]}

机构：

[1] Hong Kong Polytech Univ, Rehabil Engn Ctr, Hong Kong, Peoples R China

来源：

PROCEEDINGS OF THE 20TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOL 20, PTS 1-6: BIOMEDICAL ENGINEERING TOWARDS THE YEAR 2000 AND BEYOND | 1998年 / 20卷

关键词：

feature extraction; segmentation; neural network;

D O I：

暂无

中图分类号：

R5 [内科学];

学科分类号：

1002 ; 100201 ;

摘要：

The segmentation is an important part of the automatic or semi-automatic analysis systems of CT images. In this paper, the scheme of segmentation directly based on three-dimensional gray volume is presented. The CT slices digitized by scanner or digital camera are normalized and reconstructed to output the 3D gray volume. The 3D feature extraction reduces the correlation among voxels and emphasizes the continuity of voxels of the same tissue and the discontinuity of voxels between different tissues. A neural network of feature map classifier is used to cluster the feature volumes. The results show the difference between the segmentation based on 3D and 2D features.

引用

页码：605 / 608

页数：4

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