Speckle Reduction of Ultrasound Image Using Wavelet Transform

<p>Ultrasonography is often more desirable than another medical imaging formations because it is non-invasive, portable and utilizable. It does not use ionizing radiations and it is comparatively low-cost. In time, the main disadvantage of medical ultrasonography is the poor quality of images, which are mainly originated by multiplicative speckle noise. For efficient speckle suppression of images of the kidney a comparison of some noise reduction method is introduced in this paper. The main intention of this paper is to analyse and to provide most significant content descriptive parameters to identify and classify the kidney stones with ultrasound scan. The intentions of the present study were to compare quantitative and qualitative ultrasound highly improved images by reducing speckle noise while improving anatomical features, so that the images may be acceptable for the diagnosis. For efficient image improvement we adopt a multi-resolution approach. For speckle reduction, many algorithms and procedures are used. Some filtering technique enhances edges and speckle indiscriminately, while others manages to remove considerable amounts of speckle but also tends to over smooth the boundaries of important image features. For 2-dimensional B-mode ultrasound images, we use an image enhancement algorithm based on filtering and noise reduction procedures from the pinguid to fine resolution images that are obtained from the wavelet-transformed data. In this paper, a comparative study with other de-speckling techniques (median and Wiener filtering) is made employing quantitative indices and visual evaluation that demonstrates that our method achieved superior speckle reduction performance.