The effect of 1 024×1 024 reconstruction matrix combined with Karl iterative reconstruction algorithm on adrenal gland image quality and auto-segmentation in CT images
10.3969/j.issn.1002-1671.2024.08.032
- VernacularTitle:1 024×1 024重建矩阵结合Karl迭代重建算法对肾上腺CT图像质量和自动分割的影响
- Author:
Shigeng WANG
1
;
Yijun LIU
;
Yong FAN
;
Xiaoyu TONG
;
Wei WEI
;
Yan JIANG
Author Information
1. 大连医科大学附属第一医院放射科,辽宁 大连 116011
- Keywords:
reconstruction matrix;
iterative reconstruction algorithm;
deep learning;
adrenal gland
- From:
Journal of Practical Radiology
2024;40(8):1358-1362
- CountryChina
- Language:Chinese
-
Abstract:
Objective To explore the effect of large reconstruction matrix(1 024× 1 024)combined with Karl iterative recon-struction algorithm on adrenal gland image quality and auto-segmentation in CT images.Methods Retrospective analysis was per-formed on 40 patients with adrenal gland CT enhancement.After scanning,the original data of venous phase images were reconstruc-ted and grouped.Group A was reconstructed using conventional 512X512 matrix combined with Karl 5;group B was reconstructed using 1 024X1 024 reconstruction matrix combined with Karl iterative reconstruction algorithm(level 5,7,9)of different levels,and was denoted as group B1-B3.Two radiologists assessed the display of adrenal glands,overall image quality,and auto-segmentation stability on a 5-point scale.The CT and standard deviation(SD)values of the adrenal gland and inferior vena cava in each group were measured.The signal-to-noise ratio(SNR)and contrast-to-noise ratio(CNR)were calculated.The deep learning(DL)-based organ segmentation model was used to segment the adrenal glands of each group of reconstructed images.The Dice coefficients and the vol-ume difference rates were calculated.Results In terms of the display of adrenal glands,overall image quality,and auto-segmentation stability,group B2 had the highest score and was better than group A(P＜0.05).With the increase of Karl levels,the SD values of adrenal gland and inferior vena cava in group B gradually decreased(P＜0.05),SNR and CNR gradually increased(P＜0.05),and there was no significant difference between group B2 and group A in SD value,SNR and CNR(P＞0.05).Dice coefficients of all groups＞0.90.The volume difference rate of adrenal gland(both sides)in group B was less than 5％,which was lower than that in group A(P＜0.05).Conclusion The use of a 1 024 × 1 024 reconstruction matrix combined with Karl 7 is able to optimize the qual-ity of the adrenal gland images without compromising the segmentation accuracy of the adrenal gland images.
