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Insights into Imaging
Fig. 2 | Insights into Imaging

Fig. 2

From: Deep learning image reconstruction algorithm for carotid dual-energy computed tomography angiography: evaluation of image quality and diagnostic performance

Fig. 2

Qualitative image analysis for image noise and texture between four reconstructed images. A 71-year-old male with carotid artery occlusion. The 80% ASIR-V (a), DLIR-L (b), DLIR-M (c), and DLIR-H (d) are shown. The image noise of DLIR-L seems to be similar to that of ASIR-V, but the image of DLIR-M and DLIR-H is obviously better than ASIR-V. The over-smooth “plastic-looking” texture at centrum semiovale the most striking in the ASIR-V image, while the unnatural texture was reduced in all DLIR images, especially in DLIR-H

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