scispace - formally typeset
Proceedings ArticleDOI

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

Reads0
Chats0
TLDR
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.
Abstract
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

read more

Citations
More filters
Journal ArticleDOI

Evaluation of Speckle Noise Reduction and Feature Enhancement in Prolapsed Mitral Valve Leaflet Echocardiography

TL;DR: A comparative analysis of well established despeckling filters compiled for speckle suppression and feature enhancement shows that feature enhanced Fast Non-Local Means (FNLM) filter outperforms other state-of-art filtering techniques in the aspect of higher PSNR value and preserves structural similarity in terms of SSIM value near to unity.
Journal ArticleDOI

Facilitating the Detection of ASD in Ultrasound Video using RHOOF and SVM

TL;DR: Support vector machine (SVM) has outperformed other technique on sensitivity and time complexity, hence chosen for abnormality classification in this work and an algorithm has been devised to use combination of RHOOF and SVM for the detection of atrial septal defect (ASD).
Related Papers (5)