A No-Reference Image Quality Metric with Application in Low-Dose Human Lung CT Image Processing

In this paper a no-reference image quality metric designed for human lung CT scans is presented. The metric can be used for several purposes, including the evaluation of visual quality of CT scans or controlling enhancement processes. The developed method is based on a modified SKFCM image segmentation algorithm combined with the SSIM metric. A lung phantom was constructed for validation purposes. Tests were performed both with synthetic images, using the lung phantom with added noise, and with real CT images. The presented methods include simulations, quantitative studies and subjective evaluation. Experimental results show that the metric values reliably follow the visual image quality of CT.<br />

Abstract licence: CC BY-SA

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