A novel hybrid algorithm for accelerating CT reconstructions and improving low-dose image quality

Author

Do, Synho ; Karl, W. Clem ; Pien, Homer

Author_Institution

Massachusetts Gen. Hosp., Boston, MA, USA

fYear

2011

fDate

March 30 2011-April 2 2011

Firstpage

1516

Lastpage

1519

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.

Keywords

computerised tomography; data analysis; feature extraction; filtering theory; image denoising; image fusion; image reconstruction; image resolution; image texture; iterative methods; medical image processing; CT reconstruction hybrid algorithm; filtered-back projection images; low-dose abdominal CT data analysis; low-dose image quality; multiresolution feature fusion; noise suppression; nonquadratic regularized iterative reconstruction; textural qualities; Computed tomography; Image reconstruction; Iris; Noise; Protocols; Reconstruction algorithms; Iterative reconstruction technique; Low dose imaging; MRFF; cone beam spiral;

fLanguage

English

Publisher

ieee

Conference_Titel

Biomedical Imaging: From Nano to Macro, 2011 IEEE International Symposium on

Conference_Location

Chicago, IL

ISSN

1945-7928

Print_ISBN

978-1-4244-4127-3

Electronic_ISBN

1945-7928

Type

conf

DOI

10.1109/ISBI.2011.5872689

Filename

5872689