Which technique improves the signal-to-noise ratio in ultrasound imaging?

Which technique improves the signal-to-noise ratio in ultrasound imaging?

• A. Edge enhancement
• B. Dynamic range
• C. Gray scale
• D. Frame averaging

Answer: (D)

Improving the signal-to-noise ratio in ultrasound imaging comes from reducing random noise by averaging multiple acquisitions. Frame averaging does exactly that by combining several consecutive frames into one image. Because the tissue signal remains consistent while noise fluctuates randomly from frame to frame, averaging dampens those random fluctuations and raises the SNR. The gain in SNR is roughly proportional to the square root of the number of frames averaged, so more frames give a cleaner image. However, this approach reduces temporal resolution; you need more frames to compute the average, which can blur moving structures. Edge enhancement sharpens boundaries but can also boost noise and doesn’t actually increase the underlying SNR. Dynamic range affects how much contrast you can display but not the intrinsic noise level of the acquired data. Gray scale determines how many intensity levels are shown, which changes image appearance but not the noise characteristics of the signal.

Improving the signal-to-noise ratio in ultrasound imaging comes from reducing random noise by averaging multiple acquisitions. Frame averaging does exactly that by combining several consecutive frames into one image. Because the tissue signal remains consistent while noise fluctuates randomly from frame to frame, averaging dampens those random fluctuations and raises the SNR. The gain in SNR is roughly proportional to the square root of the number of frames averaged, so more frames give a cleaner image.

However, this approach reduces temporal resolution; you need more frames to compute the average, which can blur moving structures. Edge enhancement sharpens boundaries but can also boost noise and doesn’t actually increase the underlying SNR. Dynamic range affects how much contrast you can display but not the intrinsic noise level of the acquired data. Gray scale determines how many intensity levels are shown, which changes image appearance but not the noise characteristics of the signal.