Computed tomography (CT) is a medical imaging technique which is widely used in various clinical applications. Since the applied radiation is potentially harmful to humans, the applied doses are carefully monitored during CT image acquisition. On the contrary, the CT image quality is not analyzed or monitored during normal clinical operation. A wide range of parameters such as patient anatomy, implants, cardiac or respiratory motion, pathological tissue variations or an inappropriately configured CT system can affect the image quality. Hence, an automated image quality assessment would be desirable to track the CT image quality in daily clinical routine. In this work, the image noise and spatial resolution were characterized and analyzed in order to determine the image quality. While the image noise was characterized by the noise power spectrum (NPS), the spatial resolution was described by the modulation transfer function (MTF). Both methods were applied to human torso phantom images or real thorax CT images. It was shown that both parameters are useful to distinguish between different image qualities. Lower CT image quality was correlated with higher noise amplitudes (measured by the NPS) and a lower spatial resolution (measured by the MTF). Challenges for future works remain in generating appropriately annotated clinical CT image databases as well as in automatically selecting suitable regions-of-interest within the image.