Noise Reduction in Mri Images
نویسنده
چکیده
Real world signals usually contain departures from the ideal signal that would be produced by our model of the signal production process. Such departures are referred to as noise. Noise arises as a result of unmodelled processes going on in the production and capture of the real signal. It is not part of the ideal signal and may be caused by a wide range of sources, e.g. variations in the detector sensitivity, environmental variations, the discrete nature of radiation, transmission or quantization errors, etc. It is also possible to treat irrelevant scene details as if they are image noise. The characteristics of noise depend on its source, as does the operator which best reduces its effects. In this study, we have tried to analyze the different types of noises present in MRI images and to filter these noises using different digital filters. In the given figure, we added poisson, salt & pepper, speckle, Gaussian, additive Gaussian and multiplicative Gaussian noise. In the present study, we quantitatively establish the use of various parameters which helps in analysing the filter performance that are otherwise difficult to determine by other classical methods of image processing. This study investigates which type of filter removes or reduces which noise properly and if combination of filters are used then which type of filters give the desired results. The present study focuses on max, min, median, cumulative mean, bilateral and Gaussian filter. The parameters which determine the filter performance are The first chapter is the introduction to digital image processing and focuses on basic characteristics of image. The second chapter is based on image noise, in which the concept of image noise is briefed and various types of noise are discussed. The next chapter deals with the magnetic resonance imaging process in detail. The fourth chapter is based on noise filtering and various filters are discussed. The next chapter is based on the methodology used in this work. It basically gives the method used to complete this work. The last chapter concludes with the results and the conclusion with the future scope of the work.
منابع مشابه
An Adaptive Hierarchical Method Based on Wavelet and Adaptive Filtering for MRI Denoising
MRI is one of the most powerful techniques to study the internal structure of the body. MRI image quality is affected by various noises. Noises in MRI are usually thermal and mainly due to the motion of charged particles in the coil. Noise in MRI images also cause a limitation in the study of visual images as well as computer analysis of the images. In this paper, first, it is proved that proba...
متن کاملA Bayesian approach for image denoising in MRI
Magnetic Resonance Imaging (MRI) is a notable medical imaging technique that is based on Nuclear Magnetic Resonance (NMR). MRI is a safe imaging method with high contrast between soft tissues, which made it the most popular imaging technique in clinical applications. MR Imagechr('39')s visual quality plays a vital role in medical diagnostics that can be severely corrupted by existing noise duri...
متن کاملAssessment of the Wavelet Transform for Noise Reduction in Simulated PET Images
Introduction: An efficient method of tomographic imaging in nuclear medicine is positron emission tomography (PET). Compared to SPECT, PET has the advantages of higher levels of sensitivity, spatial resolution and more accurate quantification. However, high noise levels in the image limit its diagnostic utility. Noise removal in nuclear medicine is traditionally based on Fourier decomposition o...
متن کاملShearlet-Based Adaptive Noise Reduction in CT Images
The noise in reconstructed slices of X-ray Computed Tomography (CT) is of unknown distribution, non-stationary, oriented and difficult to distinguish from main structural information. This requires the development of special post-processing methods based on the local statistical evaluation of the noise component. This paper presents an adaptive method of reducing noise in CT images employing th...
متن کاملروشی نوین در کاهش نوفه رایسین از مقدار بزرگی سیگنال دیفیوژن در تصویربرداری تشدید مغناطیسی (MRI)
The true MR signal intensity extracted from noisy MR magnitude images is biased with the Rician noise caused by noise rectification in the magnitude calculation for low intensity pixels. This noise is more problematic when a quantitative analysis is performed based on the magnitude images with low SNR(<3.0). In such cases, the received signal for both the real and imaginary components will fluc...
متن کاملSpeckle Noise Reduction for the Enhancement of Retinal Layers in Optical Coherence Tomography Images
Introduction One of the most important pre-processing steps in optical coherence tomography (OCT) is reducing speckle noise, resulting from multiple scattering of tissues, which degrades the quality of OCT images. Materials and Methods The present study focused on speckle noise reduction and edge detection techniques. Statistical filters with different masks and noise variances were applied on ...
متن کامل