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.
Artículo
en Chino
| WPRIM
| ID: wpr-239174
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:
Disponible
Índice:
WPRIM (Pacífico Occidental)
Asunto principal:
Procesamiento de Imagen Asistido por Computador
/
Tomografía Computarizada por Rayos X
/
Artefactos
Límite:
Humanos
Idioma:
Chino
Revista:
Journal of Southern Medical University
Año:
2015
Tipo del documento:
Artículo
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