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. Experimental results show that the values of the metric reliably follow the visual image quality of CT.