Image denoising could be a major concern within the field of medical imaging. An ultrasound is also referred to as ultrasonography, which is a device that is used to create images of the inner body by using high frequency sound waves. Ultrasound is an imaging technique which is noninvasive, nonradioactive and also inexpensive and is used for diagnosis and treatment. Presence of noise in ultrasound images is a major issue as it can lead to improper diagnosis of the disease. It is very important to restore the quality of the images so as to gain information from the medical images. It is important to preserve the features of the image by reducing the noise levels. This work explains about the various kinds of noises present within the ultrasound medical images and also the filters that are used for the noise removal purpose. The noises were introduced in the ultrasound images are Salt and Pepper Noise (impulse or spike noise), Poisson noise (shot noise), Gaussian or amplifier noise and Speckle Noise. For the noise reduction from ultrasound images, a study is carried out by using Gaussian filter, bilateral filter, Order statistic filter, Mean filter and Laplacian filter for efficient noise reduction from the images. The results we obtained after performing the experiments shows the performance and comparisons of different filters supported their PSNR (Peak signal to noise ratio), MSE (Mean Square Error), and RMSE (Root Mean Square Error) values. This paper explains about the Image Noises and Filtering techniques used in effective removal of the Image Noises and performance of different Filters is analyzed on the basis of the PSNR, MSE and RMSE values.