After scanning a very large patient, how can a radiologist request new images with decreased image noise?

After scanning a very large patient, how can a radiologist request new images with decreased image noise?

• A. Reconstructing with more edge-enhancement
• B. Adjusting the window width (WW)
• C. Adjusting the window level (WL)
• D. Reconstructing thicker slices

Answer: (D)

When scanning a very large patient, the radiologist can request new images with decreased image noise by reconstructing thicker slices. Thicker slices can lead to reduced noise because they increase the amount of data collected from the patient in each slice, averaging out some of the random variations in signal that contribute to noise. This averaging effect can enhance the overall image quality while reducing the visibility of noise artifacts. In the context of CT imaging, thicker slices mean that the system gathers more photons during each scan section, which boosts the signal-to-noise ratio. A higher signal-to-noise ratio results in images that are clearer and contain less graininess, enhancing the diagnostic value of the scans produced for large patients. Other methods, like edge-enhancement, do not inherently decrease image noise; they may actually highlight noise and artifacts instead. Adjusting window width and level affects the contrast and brightness of the images, which might improve visibility but will not directly address the underlying noise in the reconstructed images. Thus, using thicker slices is the preferred method to specifically decrease image noise after scanning a very large patient.

When scanning a very large patient, the radiologist can request new images with decreased image noise by reconstructing thicker slices. Thicker slices can lead to reduced noise because they increase the amount of data collected from the patient in each slice, averaging out some of the random variations in signal that contribute to noise. This averaging effect can enhance the overall image quality while reducing the visibility of noise artifacts.

In the context of CT imaging, thicker slices mean that the system gathers more photons during each scan section, which boosts the signal-to-noise ratio. A higher signal-to-noise ratio results in images that are clearer and contain less graininess, enhancing the diagnostic value of the scans produced for large patients.

Other methods, like edge-enhancement, do not inherently decrease image noise; they may actually highlight noise and artifacts instead. Adjusting window width and level affects the contrast and brightness of the images, which might improve visibility but will not directly address the underlying noise in the reconstructed images. Thus, using thicker slices is the preferred method to specifically decrease image noise after scanning a very large patient.