Ultrasound is a well-known medical imaging modality on its ability to visualize kidney, liver and pancreas accurately. However, speckle noise, caused by constructive and destructive interferences of the wavelets will disturb the image of the organs. The main goal of this paper is to identify the most suitable and reasonable filtering technique for each organ. 50 ultrasound images for each organ- kidney, liver and pancreas are taken using Toshiba Nemio 10 ultrasound machine with 3.75 MHz PVM-375AT transducer. The images are cropped into specific sizes before converted into grayscale image. Each of the images then filtered using median filter, Wiener filter, 2-D order-statistic filter, N-D filter, and Entropy filter. Performance of each filter are analysed with MSE and PSNR. The results show that Median filter is the most suitable filter for kidney and pancreas while Wiener filter is the most effective filter in removing noise for liver.

Filtering technique in ultrasound for kidney, liver and pancreas image using Matlab

Objective: This article proposes a new edge preserving method for suppressing the noises in liver CT images. Methods/ Statistical Analysis: The MATLAB platform is used for implementation of proposed method. For Performance evaluation Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR) and time complexity are chosen .Noisy abdominal CT images have taken as input for proposed method and for finding low error and high noise fidelity. Findings: In this article, the proposed method Edge Preserving Hybrid filter have applied in liver CT images for improving the classification of lesions areas in an infected liver. The advantage of our proposed method is compared with various DE noising filters using quality metrics such as Image enhancement factor, and metric to measure the Structural similarity index and helps in the assessment of image quality and fidelity. Application/Improvement: The proposed techniques give better PSNR and it takes less simulation time in removing noises from Liver CT images.

New Edge Preserving Hybrid Method for Better Enhancement of Liver CT Images

The liver is the largest organ of the body, located in the upper left of the abdomen and performs various important functions like clearing toxins from the blood, production of blood proteins and bile to help in digestion. However, liver diseases are one of the leading causes of deaths worldwide. In a CT scan, indications of cancer presence can be Identified by a difference in pixel intensity from that of the liver. Manual segmentation and classification of CT scans are laborious and time-consuming for a clinical setting. Automatic segmentation, on the other hand, is a very challenging task, due to various factors. Our proposed system is focused on detection of anomalies present in the liver. As a first step, Liver CTscan image is acquired. Then the disease present in the liver is segmentation using binary tree quantization. By extracting features such as Pyramid Histogram of Oriented Gradients (PHOG) and Gray level Run Length Matrix (GLRLM) from the segmented region. Keywords—liver, segmentation,binary tree quantization, Pyramid Histogram of Oriented Gradients (PHOG), Gray level Run Length Matrix (GLRLM)

/pdf/analysis-of-liver-anomalies-in-ct-image-using-feature-neq3y7xp2v.pdf

Analysis of Liver Anomalies in CT Image Using Feature Extraction Method GLRLM and PHOG Algorithm

The ultrasound imaging technique is used to identify abnormalities of the kidney. The kidney may contain abnormalities, e.g. kidney swelling, change in its position and appearance. Kidney abnormality may also appear due to cysts, cancerous cells, congenital anomalies, blockage of urine, etc. To operate abnormal kidney, it is required to detect the exact and accurate place of cyst in the kidney. The ultrasound images have low contrast and mainly contain speckle noise which creates a challenging task in kidney abnormalities detection. Thus preprocessing of ultrasound images is an important task to remove speckle noise. In preprocessing, to reduce speckle noise Gaussian filter is applied the resultant image is enhanced using histogram equalization. The preprocessed ultrasound image is segmented using Gradient Vector Flow (GVF) segmentation. This external force (i.e., GVF) was calculated gradient vectors of gray level and binary edge map.

Detection and Segmentation of Kidney from Ultrasound Image Using GVF

Amongst many imaging modalities available now a days, Ultrasound is the most widely used because of the reasons like radiation free, real time, non-invasive and non-ionizing During patient’s care, medical images, videos & other physiological signals, become an integral part of diagnostic and treatment phases Ultrasound is more advantageous and cheaper than other modalities like MRI, CT, PET Speckle noise present in US hampers the quality of images which in turn considerably increases the difficulty in medical visual inspection The diagnostic accuracy will be more if image is less noisy, this necessitates the use of efficient despeckling filter which will take care of edge detection, loss of information and improve visual evaluation MSE assess the image quality, if the value is high then image quality is poor PSNR is another quality metrics, high value indicates the better denoising algorithm In the present work seven different filters are listed and experimental work is carried out on LEE and Hybrid Median filter (HMF) The experimental result of PSNR and MSE values are considered for evaluation purpose

Efficient Speckle Reduction Techniques in Ultrasound Video Quality Enhancement – A Comparative Evaluation

It is well-known that noise degrades the visual evaluation in ultrasound imaging. Speckle noise is the most common form of noise present in US images.Fast, portable, inexpensive andcapable of real time imaging, but unfortunately, however, accurateultrasound images, lack useful conclusions from the images due to noise degradations. In this paper we are evaluating and comparing the different denoising filters based on requirements in medical science according to their applications,merits and demerits.This review paper gives the analysis of selection of proper filter according to the required parameters for best result and at the same time their comparative study enhances the selection of proper filter as per requirement.

Sobika Ambardar

Papers

A Review and Comparative Study of De-noising Filters in Ultrasound Imaging