Summary: Ultrasonography is often preferred over other medical imaging modalities because it is noninvasive, portable, and versatile, it does not use ionizing radiations, and it is relatively low-cost. However, the main disadvantage of medical ultrasonography is the poor quality of images, which are affected by multiplicative speckle noise. Speckle occurs especially in images of the liver and kidney whose underlying structures are too small to be resolved by large wavelength ultrasound. The presence of speckle is undesirable since it degrades image quality and it affects the tasks of human interpretation and diagnosis. As a result, speckle filtering is a critical pre-processing step for feature extraction, analysis, and recognition from medical imagery measurements.
For 2-dimensional B-mode ultrasound images, we use an image enhancement algorithm based on filtering and noise reducing procedures from the coarse to fine resolution images that are obtained from the wavelet-transformed data. A comparative study with other despeckling techniques (median and Wiener filtering), employing quantitative indices and visual evaluation, demonstrates that our method achieves superior speckle reduction performance.