An iterative projection-based motion estimation and compensation scheme for head x-ray CT

Purpose: Although current computed tomography (CT) systems can scan the head in a very short time, patient motion sometimes still induces artifacts. If motion occurs, one has to repeat the scan; to avoid motion, sedation or anesthesia is sometimes applied. Methods: The authors propose a method to it...

Full description

Saved in:
Bibliographic Details
Published in:Medical physics (Lancaster) Vol. 43; no. 10; pp. 5705 - 5716
Main Authors: Sun, Tao, Kim, Jung-Ha, Fulton, Roger, Nuyts, Johan
Format: Journal Article
Language:English
Published: United States American Association of Physicists in Medicine 01.10.2016
Subjects:
Analysis of motion
Biological material, e.g. blood, urine; Haemocytometers
Computed tomography
Computerised tomographs
computerised tomography
Digital computing or data processing equipment or methods, specially adapted for specific applications
General statistical methods
Humans
Image data processing or generation, in general
Image enhancement or restoration, e.g. from bit‐mapped to bit‐mapped creating a similar image
Image Processing, Computer-Assisted - methods
Image reconstruction
image resolution
image restoration
Image scanners
iterative methods
iterative reconstruction
Kinematics
mean square error methods
Medical image artifacts
medical image processing
Medical image reconstruction
motion compensation
motion estimation
Movement
Movement sensors
phantoms
Phantoms, Imaging
Reconstruction
rigid motion
Spatial resolution
Tomography, X-Ray Computed
computed tomography
motion estimation
iterative reconstruction
rigid motion
motion compensation
ISSN:0094-2405, 2473-4209, 2473-4209
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Purpose: Although current computed tomography (CT) systems can scan the head in a very short time, patient motion sometimes still induces artifacts. If motion occurs, one has to repeat the scan; to avoid motion, sedation or anesthesia is sometimes applied. Methods: The authors propose a method to iteratively estimate and compensate this motion during the reconstruction. In every iteration, the rigid motion was estimated view-by-view and then used to update the system matrix. A multiresolution scheme was used to speed up the convergence of this joint estimation of the image and the motion of the subject. A final iterative reconstruction was performed with the last motion estimate. Results: The method was evaluated on simulations, patient scans, and a phantom study. The quality of the reconstructed images was improved substantially after the compensation. In simulation and phantom studies, root-mean-square error was reduced and mean structural similarity was increased. In the patient studies, most of the motion blurring in the reconstructed images disappeared after the compensation. Conclusions: The proposed method effectively eliminated motion-induced artifacts in head CT scans. Since only measured raw data are needed for the motion estimation and compensation, the proposed method can be applied retrospectively to clinical helical CT scans affected by motion.
Bibliography:tao.sun@uzleuven.be
Electronic mail
ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:0094-2405
2473-4209
2473-4209
DOI:10.1118/1.4963218