A brief review on speckle noise reduction techniques for ultrasound images

Speckle noise, typically occurs in coherent imaging systems such as sonar, laser and ultrasound imaging, is an unwanted aftereffect of the image formation process in coherent imaging .Speckle reduction is an important issue for analysis of ultrasound images. In  ultrasound imaging system, the presence of speckle results decline  in image quality and makes it difficult for human interpretation and  diagnosis analysis.Numerous methods for speckle suppression were proposed. In this paper we have given the overview of  the speckle noise reduction modelalong with various filters which are commonly used for speckle reduction needed in ultrasound images. As speckle noise is dominated in ultrasound imaging, there is need of de-noising the ultrasound images before segmenting out the tumor regions. As border detection of these tumors should be highly accurate as final results of segmentation are dependent on it. Further we will explore the tumor edge detection and segmentation of infected liver ultrasound images

Non-intrusive measurements of wave-induced flow over dikes by means of a combined ultrasound doppler velocimetry and videography

The performance of non-intrusive instruments, such as acoustic profilers and cameras, to describe the wave-induced flow processes over maritime dike crest was investigated in experiments carried out at the University of Bologna. Direct and derived measurements from the acoustic probes deployed along the structure crest were discussed in relation to the observed backscatter rates. Image processing was implemented by means of clustering algorithm, in order to detect the free surface during overtopping events and characterize wave front propagation over the dike crest. UVP data were processed to indirectly derive flow depths and overtopping rates and compare them with the direct measurements in order to assess the measurement reliability and discuss their limits. Individual overtopping volume distribution as obtained by UVP data were estimated and compared with well-consolidated formulations, showing a good agreement. Finally, suggestions for an appropriate use of non-intrusive instruments to characterize a shallow, transient and aerated flow were provided, such as the control of the artificial seeding density, the use of a bi-static UVP configuration and adjustments to light exposure

Image segmentation and reconstruction of 3D surfaces from carotid ultrasound images

Tese de doutoramento. Engenharia Electrotécnica e de Computadores. Faculdade de Engenharia. Universidade do Porto. 200

Multi-level Trainable Segmentation for Measuring Gestational and Yolk Sacs from Ultrasound Images

As a non-hazardous and non-invasive approach to medical diagnostic imaging, ultrasound serves as an ideal candidate for tracking and monitoring pregnancy development. One critical assessment during the first trimester of the pregnancy is the size measurements of the Gestation Sac (GS) and the Yolk Sac (YS) from ultrasound images. Such measurements tend to give a strong indication on the viability of the pregnancy. This paper proposes a novel multi-level trainable segmentation method to achieve three objectives in the following order: (1) segmenting and measuring the GS, (2) automatically identifying the stage of pregnancy, and (3) segmenting and measuring the YS. The first level segmentation employs a trainable segmentation technique based on the histogram of oriented gradients to segment the GS and estimate its size. This is then followed by an automatic identification of the pregnancy stage based on histogram analysis of the content of the segmented GS. The second level segmentation is used after that to detect the YS and extract its relevant size measurements. A trained neural network classifier is employed to perform the segmentation at both levels. The effectiveness of the proposed solution has been evaluated by comparing the automatic size measurements of the GS and YS against the ones obtained gynaecologist. Experimental results on 199 ultrasound images demonstrate the effectiveness of the proposal in producing accurate measurements as well as identifying the correct stage of pregnancy

Feature point detection in HDR images based on coefficient of variation

Feature point (FP) detection is a fundamental step of many computer vision tasks. However, FP detectors are usually designed for low dynamic range (LDR) images. In scenes with extreme light conditions, LDR images present saturated pixels, which degrade FP detection. On the other hand, high dynamic range (HDR) images usually present no saturated pixels but FP detection algorithms do not take advantage of all the information present in such images. FP detection frequently relies on differential methods, which work well in LDR images. However, in HDR images, the differential operation response in bright areas overshadows the response in dark areas. As an alternative to standard FP detection methods, this study proposes an FP detector based on a coefficient of variation (CV) designed for HDR images. The CV operation adapts its response based on the standard deviation of pixels inside a window, working well in both dark and bright areas of HDR images. The proposed and standard detectors are evaluated by measuring their repeatability rate (RR) and uniformity. Our proposed detector shows better performance when compared to other standard state-of-the-art detectors. In uniformity metric, our proposed detector surpasses all the other algorithms. In other hand, when using the repeatability rate metric, the proposed detector is worse than Harris for HDR and SURF detectors

A Tutorial on Speckle Reduction in Synthetic Aperture Radar Images

Speckle is a granular disturbance, usually modeled as a multiplicative noise, that affects synthetic aperture radar (SAR) images, as well as all coherent images. Over the last three decades, several methods have been proposed for the reduction of speckle, or despeckling, in SAR images. Goal of this paper is making a comprehensive review of despeckling methods since their birth, over thirty years ago, highlighting trends and changing approaches over years. The concept of fully developed speckle is explained. Drawbacks of homomorphic filtering are pointed out. Assets of multiresolution despeckling, as opposite to spatial-domain despeckling, are highlighted. Also advantages of undecimated, or stationary, wavelet transforms over decimated ones are discussed. Bayesian estimators and probability density function (pdf) models in both spatial and multiresolution domains are reviewed. Scale-space varying pdf models, as opposite to scale varying models, are promoted. Promising methods following non-Bayesian approaches, like nonlocal (NL) filtering and total variation (TV) regularization, are reviewed and compared to spatial- and wavelet-domain Bayesian filters. Both established and new trends for assessment of despeckling are presented. A few experiments on simulated data and real COSMO-SkyMed SAR images highlight, on one side the costperformance tradeoff of the different methods, on the other side the effectiveness of solutions purposely designed for SAR heterogeneity and not fully developed speckle. Eventually, upcoming methods based on new concepts of signal processing, like compressive sensing, are foreseen as a new generation of despeckling, after spatial-domain and multiresolution-domain method

Адаптивний метод фільтрації УЗД-зображення на основі анізотропної дифузії

Запропоновано адаптивний фільтр спекл-шуму на основі використання анізотропної дифузії, що використовує локальну статистику для визначення примежових ділянок об’єктів на зображенні та змінює глибину фільтрації, відповідно до отриманих даних.Предложен адаптивный фильтр спекл-шума с использованием анизотропной дифузии, который использует локальную статистику для определения приконтурных областей и изменяет глубину фильтрации, согласно полученным данным.An adaptive filter for despeckling based on anisotropic diffusion is developed. Filter uses local statistics for defining edge areas and changes the depth of filtering according to these information