IJIRST –International Journal for Innovative Research in Science & Technology| Volume 1 | Issue 8 | January 2015 ISSN (online): 2349-6010 All rights reserved by www.ijirst.org 21 Denoising of Computed Tomography Images using Wavelet Transform Savita Verma Navdeep Khare Department of Electronics and Telecommunication Department of Electronics and Telecommunication SSEC, Bhilai(C.G.), 490020 SSEC, Bhilai(C.G.), 490020 Abstract Image denoising is one of the most significant tasks in image processing, analysis and image processing applications. Medical Imaging is one among the emerging application areas where the image denoising plays a vital role. In medical imaging, the additional techniques and systems introduce noises and artifacts in the medical image that leads to poor quality image. In this moment, image denoising is an essential pre-requisite, specially in Computed Tomography, which is an important and most common method in medical imaging. The significance of the denoising is mainly due to that the effectiveness of clinical diagnosis using CT image depends upon the quality of the image. In this work, we propose an efficient noise reduction technique for CT images using wavelet transformation and thresholding. The technique removes Additive noise from the CT images as well as it enhances the quality of the images. Keywords: Continuous Wavelet Transform, Digital Imaging And Communications In Medicine, Discrete Wavelet Transform. _______________________________________________________________________________________________________ I. INTRODUCTION Digital signal processing (DSP) describes the science that tries to evaluate, generate and manipulate measured real world signals with the help of a digital computer. signals can be anything that is a collection of numbers, or measurements and the most commonly used signals include images, audio (such as digitally recorded speech and music) and medical and seismic data. The Fourier transform (FT) is probably the most popular transform used to obtain the frequency spectrum of a signal. Noise removal or de-noising is an important task in image processing. Image enhancement is a collection of techniques that improve the quality of the given image that is making certain features of the image easier to see or reducing the noise. In general, the results of the noise removal have a strong influence on the quality of the image processing techniques. Noise generated by electronic components in instrumentation is a common type of random signal that is present in much biomedical data even though contemporary electronic design minimizes this noise. Often those components of a signal which are not understood are classified as noise. The ultimate base for deciding what constitutes noise should be derived from considerations about the experimental or clinical measurements and the source of a signal. Ideally when a prior knowledge for judging whether certain components of a signal represent the desired measurement or not is known then the signal processing method is chosen to enhance the desired signal and reduce undesired signal components. In some cases this information may not be known and it may be necessary to examine the results of the signal processing steps to assess whether the output signal exhibits some apparent separation into desired and noise components. The field of imaging provides many examples of both biomedical images and biomedical image processing. Computed Tomography (CT) image is excellent for showing abnormalities of the brain such as: stroke, hemorrhage, tumor, multiple sclerosis or lesions. In the CT basic signals are currents induced in a coil caused by the movement of molecular dipoles as the molecules resume a condition of random orientation after having been aligned by the imposed magnetic field. Signal processing is needed to detect and decode them, which is done in terms of the spatial locations of the dipoles (which is related to the type of tissue in which they are located). Much of the joint signal processing is based on Fourier transform. Since CT utilizes two- dimensional Fourier transforms the basic concepts are the same CT Imaging A. Computed Tomography (CT) image scan is an imaging technique used primarily in medical field to produce high quality images of the soft tissues of the human body. Using brain images acquired by CT often allows physicians and engineers to analyze the brain without the need for invasive surgery. Other types of imaging mdalities which exist include ultrasound imaging, X-ray imaging, Magnetic resonance imaging (MRI).CT combines X-ray machine with an advanced computer system and radio waves to produce correct, detailed pictures of organs and tissues in order to diagnose a variety of medical conditions. There are two types of CT exams namely the high-field CT and low-field open CT. The difference is in that high-field CT produces a highest quality image in the shortest time allowing a most accurate diagnosis to be made. Since CT can give high quality clear pictures of soft-tissue structures near and around bones, it is the most sensitive exam for brain, spinal and joint problems. CT is widely