4D Cone-beam CT reconstruction using a motion model based on principal component analysis.

ABSTRACT:

Purpose

To provide a proof of concept validation of a novel 4D cone-beam CT (4DCBCT) reconstruction algorithm and to determine the best methods to train and optimize the algorithm.

Methods

The algorithm animates a patient fan-beam CT (FBCT) with a patient specific parametric motion model in order to generate a time series of deformed CTs (the reconstructed 4DCBCT) that track the motion of the patient anatomy on a voxel by voxel scale. The motion model is constrained by requiring that projections cast through the deformed CT time series match the projections of the raw patient 4DCBCT. The motion model uses a basis of eigenvectors that are generated via principal component analysis (PCA) of a training set of displacement vector fields (DVFs) that approximate patient motion. Th

SUBMITTER: Staub D 

PROVIDER: S-EPMC3247929 | biostudies-literature | 2011 Dec

REPOSITORIES: biostudies-literature