Open AccessNoise reduction in material decomposition for low-dose dual-energy cone-beam CT
Author(s) -
Wojciech Zbijewski,
Grace J. Gang,
Adam Wang,
J. Webster Stayman,
Katsuyuki Taguchi,
John A. Carrino,
Jeffrey H. Siewerdsen
Publication year - 2013
Publication title -
proceedings of spie, the international society for optical engineering/proceedings of spie
Language(s) - English
Resource type - Conference proceedings
SCImago Journal Rank - 0.192
H-Index - 176
eISSN - 1996-756X
pISSN - 0277-786X
DOI - 10.1117/12.2008431
Subject(s) - iterative reconstruction , piecewise , noise reduction , regularization (linguistics) , total variation denoising , computer science , algorithm , mathematics , artificial intelligence , mathematical analysis
Dual-energy cone-beam CT (DE-CBCT) is an emerging technology with potential application in diagnostic imaging and image-guided interventions. This paper reports DE-CBCT feasibility and investigates decomposition algorithms for maximizing low-dose performance for reconstruction-based DE decomposition. A framework of binary decision theory is used to examine the accuracy of DE decompositions obtained from analytical reconstructions of differentially filtered low-energy (LE) and high-energy (HE) data and from penalized likelihood (PL) reconstructions with differential regularization using quadratic and total variation penalties.