A Correlation and LS-SVM based approach to Mitigate Motion Artifacts in FDK Based 3D Cone-beam Tomography

被引：0

作者：

Bhowmik, Ujjal Kumar ^{[1
]}

Adhami, Reza R. ^{[1
]}

机构：

[1] Univ Alabama, Dept Elect & Comp Engn, Huntsville, AL 35899 USA

来源：

2011 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC) | 2011年

关键词：

Three-dimensional CT; Motion Detection; Motion Artifacts; FDK; LS-SVM; Time series prediction;

D O I：

暂无

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

Head motion during brain CT studies can degrade the reconstructed image by introducing distortion and loss of resolution, thereby contributing to misdiagnosis of diseases. In this paper, we have proposed a correlation coefficient and Least Squares Support Vector Machines (LS-SVM) based approach to detect and mitigate motion artifacts in FDK based three-dimensional cone-beam tomography. Motion is detected using correlation between adjacent x-ray projections. Artifacts, caused by motion, are mitigated either by replacing motion corrupted projections with their counterpart 180 degrees apart projections under certain conditions, or by estimating motion corrupted projections using LS-SVM based time series prediction. The method has been evaluated on 3D Shepp-Logan phantom. Simulation results validate our claims.

引用

页码：8471 / 8474

页数：4