Widely Used And Safe Medical Diagnostic Technique For Ultrasound Imaging

Ultrasound imaging is a widely used and safe medical diagnostic technique, due to its non-invasive nature, low cost and capability of forming real time imaging. Ultrasound imaging uses high- frequency sound to image internal structures by differing reflection signals produced when a beam of sound is projected into the body and bounces back at interfaces between the structures. Ultrasound imaging is used for diagnosis provides the internal structure of the body to detect eventually diseases or abnormalities tissue. Ultrasound imaging plays a crucial role in medical field to estimate kidney size, position, appearance and helps to detect structural abnormalities as well as the presence of cysts, stones, cancer, congential anomalies , swelling,

Many people are affected by chronic kidney failure due to diabetes mellitus and hypertension etc. Worldwide research indicates that one out of 10 adults has kidney problems and by 2015 it is estimated that about 36 premature deaths due to kidney disease will happen. Since kidney function impairment can be life threatening, diagnosis of the disorders and diseases in the early stages is crucial. Ultrasound is one of the non-invasive low cost widely used imaging techniques for diagnosing kidney

However, the standard weighted median filter gives a poor performance for images corrupted by impulse noise with higher intensity. A simple median filter utilizing 3x3 or 5x5 pixel window is sufficient only when the noise intensity is less than approximate 10-20%. When the intensity of noise is increasing, a simple median filter remains many shots unfiltered. Adaptive Median Filter(AMF) perform well at low noise densities. But at high noise densities the window size has to be increased which may lead to blurring the image. In switching median filter, the decision is based on a pre-defined threshold value. The major drawback of this method is that defining a robust decision is difficult. Also these filters will not take into account the local features as a result of which details and edges may not be recovered satisfactorily, especially when the noise level is high. To overcome this drawback a decision based algorithm is proposed. In this, image is denoised by using a 3x3 window. If the processing pixel value is 0 or 255 it is processed or else it is left unchanged. The selected 3x3 window elements are arranged in either increasing or decreasing order. Then the pixel values 0’s and 255’s in the image are removed from the image. Then the median value of the remaining pixels is taken. This median value is used to replace the noisy