Paper Info
Title
A novel hybrid algorithm for accelerating CT reconstructions and improving low-dose image quality
Abstract
In this paper we introduce a new algorithm for reconstruction of low-dose CT images. The approach, called multi-resolution feature fusion (MRFF), combines the textural qualities of conventional filtered-back projection images, with the noise suppression ability of non-quadratic regularized iterative reconstructions, to form a fast image reconstruction with good noise texture properties. Low-dose abdominal CT data is used to illustrate the properties of MRFF.
Year
DOI
Venue
2011
10.1109/ISBI.2011.5872689
ISBI
Keywords
Field
DocType
low-dose image quality,noise suppression,computerised tomography,filtered-back projection images,image fusion,image resolution,ct reconstruction hybrid algorithm,data analysis,image denoising,cone beam spiral,low-dose abdominal ct data analysis,multiresolution feature fusion,image reconstruction,nonquadratic regularized iterative reconstruction,mrff,feature extraction,low dose imaging,filtering theory,iterative reconstruction technique,image texture,textural qualities,iterative methods,medical image processing,filtered back projection,image quality,protocols,iterative reconstruction,noise,iris,computed tomography,hybrid algorithm
Iterative reconstruction,Computer vision,Hybrid algorithm,Pattern recognition,Image fusion,Image texture,Iterative method,Computer science,Image quality,Feature extraction,Artificial intelligence,Image resolution
Conference
ISSN
ISBN
Citations 
1945-7928 E-ISBN : 978-1-4244-4128-0
978-1-4244-4128-0
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Synho Do19412.86
W. Clem Karl222435.45
Homer Pien3446.48