Edge-detecting operator-based selection of Huber regularization threshold for low-dose computed tomography imaging / 南方医科大学学报
Journal of Southern Medical University
; (12): 375-379, 2015.
Article
em Zh
| WPRIM
| ID: wpr-239174
Biblioteca responsável:
WPRO
ABSTRACT
<p><b>OBJECTIVE</b>To compare two methods for threshold selection in Huber regularization for low-dose computed tomography imaging.</p><p><b>METHODS</b>Huber regularization-based iterative reconstruction (IR) approach was adopted for low-dose CT image reconstruction and the threshold of Huber regularization was selected based on global versus local edge-detecting operators.</p><p><b>RESULTS</b>The experimental results on the simulation data demonstrated that both of the two threshold selection methods in Huber regularization could yield remarkable gains in terms of noise suppression and artifact removal.</p><p><b>CONCLUSION</b>Both of the two methods for threshold selection in Huber regularization can yield high-quality images in low-dose CT image iterative reconstruction.</p>
Texto completo:
1
Índice:
WPRIM
Assunto principal:
Processamento de Imagem Assistida por Computador
/
Tomografia Computadorizada por Raios X
/
Artefatos
Limite:
Humans
Idioma:
Zh
Revista:
Journal of Southern Medical University
Ano de publicação:
2015
Tipo de documento:
Article