What comes to mind when you hear the term Contrast to Noise Ratio?
When radiographers perform an X-ray inspection they generate images in the process, they often seek for a way to measure the quality and accuracy of the image they get from their image producing system. Contrast to noise ratio or CNR for short gives a radiography professional a means to achieve this measurement.
CNR is simply a way of mathematically measuring the quality of an image especially when there is a notable bias in the generated image. It is a metric employed to determine how much quality an image produces during radiography.
This post helps you to understand CNR in greater depth. So, if you are ready to know more, then, let’s jump right in.
I. What is the Contrast to Noise Ratio in Radiology?
Radiology as a field has many terms individuals often find confusing and contrast to noise ratio has been one of the common confusing terms. So, what then is a contrast to noise ratio (CNR)?
Contrast to noise ratio as aforementioned is a metric utilized in calculating the quality of an image. It evaluates the contrast between the object of interest and its background.
In many quality-inspection imaging, there is usually an exchange between the noise and the mode in which the image was acquired, mostly the amount of radiation on the object of interest has to be right or the noise disrupts the quality of the image. The finest images, therefore, have a quantifiable amount of noise. Also, the skill or precision to view objects in a noisy backdrop hangs on the size of the object.
Therefore, a contrast to noise ratio is the relationship between an object of interest, the noise that surrounds this object, and the backdrop on which the object of interest has been measured or evaluated.
II. How is Contrast to Noise Ratio Calculated?
Firstly, we must consider the signal-to-noise ratio when calculating contrast to noise ratio as it enables us to acquire the necessary averages which will help calculate the contrast to noise values. And the signal to noise ratio is given as the average signal divided by the noise.
Consequently, the contrast to noise is calculated as the average contrast divided by the noise. It is also important to note that given the formulas to calculate both the signal to noise ratio and contrast to noise ratio, both ratios are significant in measuring the image quality as the numerator indicates outright contrast in connection with intensity difference which concerns its background and the object of interest.
Also, the denominator represents the image noise indicated in connection with the standard deviation of the background.
So conclusively, a signal to noise ratio is calculated as average pixel values in signal Region of Interest (ROI) divided by Standard deviation Background Region of Interest. And Contrast to Noise Ratio (CNR) is calculated as Average Signal ROI minus Average Background ROI divided by Standard deviation ROI.
III. What is the Importance of Contrast to Noise Ratio?
Since the contrast to noise ratio shows the relationship between two regions of signal intensity differences, it also translates to the fact that it Improves and increases insight on the definite differences between two regions of interest.
Therefore, it is important because it takes into consideration the measure of interest between the object of interest and its background. When too much radiation dose hits the object of interest, the noise increases, and detecting the object also becomes more tasking.
For inspections in the various industries that rely on quality imaging on inspection of components, a clear and quality image equips them with the ability to detect any defect in any of the manufactured equipment. This can only be possible with clear imaging and observation.
With accurate and precise calculations of contrast to noise ratio, they are able to make accurate decisions as it concerns its products.
Conclusion
So, in a nutshell, we have seen what contrast to noise ratio is and we have also examined signal to noise ratio and as discussed, a contrast to noise ratio is the parameter or metric employed to determine the quality of an image during an inspection.
However, one critical consideration is how to calculate the Contrast to Noise Ratio (CNR), and Contrast to Noise Ratio (CNR) is calculated as Average Signal ROI minus Average Background ROI divided by Standard deviation ROI.
Finally, CNR has been shown to have numerous benefits including the importance of Contrast to Noise Ratio and how it helps inspection officers make crucial, objective decisions when assessing and inspecting equipment for quality control and assessment.
So, next time you’re performing quality control, you might consider checking out the Contrast to Noise Ratio to ascertain the quality of image creation.
