Denoising Of Computer Tomography Images Using Wavelet Based Multiple Thresholds Switching

In accession to the binary images, the proposed method may be tested on discrete color images also. These type of

In the modern years, medical imaging has become a very important aspect of medical field since its origin in the 1970s Image processing has developed into an integral part of medical science ranging from PET scan to melanoma detection. Both the hardware and software required for Image processing have improved drastically resulting in today’s world where the medical professionals can recognise and diagnose thousands of diseases using this technology.

A method to identify DR using digital signal processing and image processing techniques has been proposed by Iqbal et.al. [iii]. The methods used by them includes colour space conversion, zero padding of image edges, median filtering and histogram equalization with overlap mean for the image pre-processing stage.

This division can be performed up to many levels. It captures not only notion of frequency content but also temporal content. Wavelets provide a mathematical way of encoding information in such a way that it is layered according to level of detail. DWT is more computationally efficient than other transformations because of its excellent localization properties. Wavelets are capable of complete lossless reconstruction of image[6].

CBCT images and found that the use of this index in CBCT images was valid;(101) however, the index obtained from CBCT images did not compare well with that derived from panoramic images, the imaging modality for which the classification was originally devised. Moreover, the CBCT analysis was conducted in templates, i.e., static slices. These aspects could have influenced the results (101).

Abstract-This paper presents the approach to analyze the ultrasound images of the patients suffering from Cholelithiasis. The occurrence of Cholelithiasis is the commonest biliary disease to be reported in India. Our research is aimed to apply the potential of image processing in diagnosing the presence of gall bladder stones. In this paper we propose a technique, a combination of preprocessing morphological techniques and Entropy calculation of the pixels representing gallstones in the gall bladder.

Computed tomography is a process by which a computer processor is able to digitally render a three-dimensional image. This technology has become mainstream in the medical field for a few decades. Millions of Computerized Tomography (CT) scans are performed in the United States annually. This technique allows medical professionals a more in-depth and precise idea of a patient's condition, and can subsequently offer further insight as to the appropriate treatments, as well as what kind of treatments may prove ineffective. Computerized tomography is a useful tool, yet it is not perfect. Unintended distortions or errors in CT scans are called artifacts. Artifacts are wholly unrelated to the patient's medical condition and may be consequence of several factors. The paper will describe how artifacts occur and propose steps by which artifacts in CT scans can be prevented or altogether avoided.

ABSTRACT: According to the report given by World Health Organization, by 2015 almost 20 million people will die from cardiovascular diseases (CVD). People in low- and middle-income countries who suffer from CVDs and other noncommunicable diseases have less access to effective and equitable health care services which respond to their needs. The main objective of this work is to develop a classifier for the diagnosis of abnormal Common Carotid Arteries (CCA). This paper proposes a new approach for the transform domain analysis of longitudinal B-mode ultrasound CCA images using Multiwavelets. Analysis is done using HM and GHM multiwavelets at various levels of decomposition. Multiwavelet preserves high frequency information in image and provides good energy compaction efficiency. Energy values of the coefficients of approximation, horizontal, vertical and diagonal details are calculated and plotted for different levels. Plots of energy values show high correlation with the abnormalities of CCA and offer the possibility of improved diagnosis of CVD. It is clear that the energy values can be used as an index of individual

Ultrasound imaging is one of the popular, cheapest and noninvasive medical scans. During the time of image acquisition, there is distortion of the quality of image in the form of speckle noise. Now a day, many researches made various experiments to enhance the quality of medical image. But still there is scope to enhance the image. In the proposed method, finding out the seed pixel randomly is basic issue, is treated as an optimization problem, it can be solved by Particle swarm optimization. Using particle swarm optimization algorithm , the fitness function can give us appropriate seed pixel for required ultrasound imaging .In this paper, a novel method wherein segmentation will be applied on the filtered image i.e fuzzy filter. Fuzzy filter basically work on fuzzy rules to detect on different gradient and then filtering the noisy , homogenous and edge region. The proposed method has been tested on different images, and the experimental results demonstrate its effectiveness.

Abstract- In medical analysis blood cell count plays vital role. Variations in the count of blood cells cause many diseases in the human body. For overall health assessment and diagnosis of many disorders complete blood count is required. Abnormal increase or decrease in cell count indicates that person has indispensable medical condition. The Complete Blood Count (CBC) is a blood test, extensively used to check various disorders such as infections, allergies, problems with clotting, anaemia, leukaemia etc. In order to perform CBC test, the blood film is stained and then imaged with a transmission light microscope. Here the analysis of the blood sample is done manually in order to count number of blood cells and also to identify disorders in blood samples through a microscope. But it is a time consuming process and also leads to undesirable human error. In essence, the goal of this review paper is to find out and validate the necessary image processing steps and different methods and algorithms used to count blood cells on blood smear slides. This paper aims to provide: mitigate problems posed by different conditions such as noisy and degraded images; detect the overlapping cells; to differentiate RBCs ,WBCs and also platelets which are present in a blood smear slide counting RBCs and WBCs and even platelets and also to detect the disease related to blood.

In my paper, two optimizations for the deconvolution will be provided by using regular iterative least square method (RILS) and iterative reweighted least square method (IRLS). By using the optimization deconvolution algorithms, we can recover the original image with more acceptable recovered image. The runtime for the original

Wavelet transform is efficient tool for image compression, Wavelet transform gives multiresolution image decomposition. which can .be exploited through vector quantization to achieve high compression ratio. For vector quantization of wavelet coefficients vectors are formed by either coefficients at same level, different location or different level, same location. This paper compares the two methods and shows that because of wavelet properties, vector quantization can still improve compression results by coding only important vectors for reconstruction.

Determination of dry and wet edges in the LST– NDVI scatter is necessary, to estimate pixel by

In NLM denoising algorithm the image is divided in to different repeated small patches. The noise can be removed and important features of the data preserved by taking advantages of the redundant information of patches. It achieves a promising result by averaging local neighborhood pixels with the similarities of the redundant patches. Each pixel of the image adjusted with a weighted average of other pixels whose neighborhoods has similar geometrical configuration. During noise attenuation method NLM algorithm also retain some important features of seismic data.

A demand for higher resolution is seen in many discipline including bio-medical imaging, satellite and astronomical imaging, chemical and military surveillance and remote sensing. But the current state of image sensor