A head motion measurement system suitable for 3D cone-beam tomography using markers.

Head motion during brain CT studies can degrade the reconstructed image through distortion and other artifacts such as blurring, doubling and thereby contributing to misdiagnosis of diseases. Estimation of motion parameters is essential for mitigating motion artifacts. In this paper, we propose a marker based numerical optimization method to measure six degrees of freedom of head motion in three-dimensional cone-beam CT system without using any external motion sensors.

Correlation and support vector machine based motion artifacts mitigation in 3D computer tomography.

Head motion during Computer Tomographic (CT) studies can adversely affects the reconstructed image through distortion and other artifacts such as blurring and doubling, thereby contributing to misdiagnosis of diseases. In this paper, we propose a method to detect and mitigate motion artifacts in three-dimensional (3D) cone-beam CT system. Motion detection is achieved by comparing the correlation coefficient between the adjacent x-ray projections.

A correlation and LS-SVM based approach to mitigate motion artifacts in FDK based 3D cone-beam tomography.

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.