What does image noise refer to in computed tomography?

Image noise in computed tomography (CT) specifically refers to undesirable fluctuations of pixel values in an image, particularly in areas that should appear uniform or homogeneous. This phenomenon can significantly affect image quality, making it challenging to interpret the data accurately. Noise can obscure fine details and lead to difficulties in distinguishing between different tissue types or pathological conditions.

In a homogeneous material, one would typically expect to see consistent pixel values that reflect its uniform density. However, presence of noise introduces random variations, which could misrepresent the true characteristics of the material being imaged. This is particularly problematic in diagnostic imaging where precision is crucial; higher noise levels can lead to misdiagnosis or oversight of critical findings.

The other choices represent different image quality issues but do not accurately define image noise. Blurring of images due to movement relates more to motion artifacts, while variations in brightness and color may pertain to contrast issues rather than noise itself. Lastly, loss of detail in low-contrast areas speaks to limitations in the system’s ability to distinguish subtle differences in tissue density but does not encapsulate the randomness characteristic of noise. Understanding these distinctions is essential for interpreting CT images effectively.