Application of knowledge-based iterative model reconstruction in patients with coronary angiography bypass grafts
HUANG Zili
LI Tao
YANG Li
LUO Chuncai
LI Xueping
LIU Bo
Abstract：Objective To investigate the value of knowledge-based iterative model reconstruction (IMR) on image quality in patients with coronary angiography bypass grafts (CABG). Methods We studied 30 patients (20 males and 10 males) with CABG using MDCT. Paired image sets were created using two types of reconstruction:hybrid iterative reconstruction(HIR) and IMR. Quantitative parameters including CT attenuation,noise,SNR and CNR of aorta,left ventricle,grafts were compared. The subjective image quality-image(noise,steak artifacts,margin sharpness of each cardiovascular structure) was compared. Results The image noise of IMR was lower than that of HIR,and SNR and CNR of IMR were better than that of HIR in all evaluate struc-tures. The visual image score was higher for IMR than for HIR. Conclusion IMR can significantly decrease the image noise and improve image quality for the patients with CABG.
Keywords：TomographyX-ray computedIterative reconstructionImage quality
Publication Date：2018-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：5( 413-417 )