Speckle Reduction In Ultrasound Images Research Articles

Speckle reducing bilateral filter for cattle follicle segmentation

BackgroundUltrasound imaging technology has wide applications in cattle reproduction and has been used to monitor individual follicles and determine the patterns of follicular development. However, the speckles in ultrasound images affect the post-processing, such as follicle segmentation and finally affect the measurement of the follicles. In order to reduce the effect of speckles, a bilateral filter is developed in this paper.ResultsWe develop a new bilateral filter for speckle reduction in ultrasound images for follicle segmentation and measurement. Different from the previous bilateral filters, the proposed bilateral filter uses normalized difference in the computation of the Gaussian intensity difference. We also present the results of follicle segmentation after speckle reduction. Experimental results on both synthetic images and real ultrasound images demonstrate the effectiveness of the proposed filter.Conclusions Compared with the previous bilateral filters, the proposed bilateral filter can reduce speckles in both high-intensity regions and low intensity regions in ultrasound images. The segmentation of the follicles in the speckle reduced images by the proposed method has higher performance than the segmentation in the original ultrasound image, and the images filtered by Gaussian filter, the conventional bilateral filter respectively.

A Motion Compounding Technique for Speckle Reduction in Ultrasound Images

The quality of ultrasound images is usually influenced by speckle noise and the temporal decorrelation of the speckle patterns. To reduce the speckle noise, compounding techniques have been widely applied. Partially correlated images scanned on the same subject cross-section are combined to generate a compound image with improved image quality. However, the compounding technique might introduce image blurring if the transducer or the target moves too fast. This blurring effect becomes especially critical when assessing tissue deformation in clinical motion examinations. In this paper, an ultrasound motion compounding system is proposed to improve the quality of ultrasound motion sequences. The proposed motion compounding technique uses a hierarchical adaptive feature weighted motion estimation method to realign the frames before compounding. Each frame is first registered and warped to the reference frame before being compounded to reduce the speckle noise. Experimental results showed that the motion could be assessed accurately and better visualization could be achieved for the compound images, with improved signal-to-noise and contrast-to-noise ratios.

Simultaneous speckle reduction and contrast enhancement for ultrasound images: Wavelet versus Laplacian pyramid

Speckle can be described as random multiplicative noise. It hampers the perception and extraction of fine details in the image. Speckle reduction techniques are applied to ultrasound images in order to reduce the noise level and improve the visual quality for better diagnoses. It is also used as preliminary treatment before segmentation and classification. Several methods have been proposed for speckle reduction in ultrasound images. Multiscale contrast enhancement has proven to be very efficient for x-ray images. A recent study by Dippel et al. doing a comparison, contrast enhancement of radiographs (x-ray and mammography), between the Laplacian pyramid and the wavelet one proves that the Laplacian pyramid method gives a better result than the wavelet one; the filtering aspect was not taken into account. In ultrasound images a strong contrast variation exists which is different from x-ray and mammography. In this paper a wavelet pyramid with simultaneous speckle reduction and contrast enhancement was applied for the first time on ultrasound images with the area of interest and compared to a Laplacian enhancement pyramid. The optimum choice of wavelet bases for ultrasound images is investigated in this study. In order to realize a fair comparison, the same nonlinear modification in both multiscale schemes is used. The comparison proves that the wavelet pyramid gives a much better result than the Laplacian one for simultaneous speckle reduction and contrast enhancement of ultrasound images.

Texture-Oriented Anisotropic Filtering and Geodesic Active Contours in Breast Tumor Ultrasound Segmentation

In this paper we present an anisotropic filter for speckle reduction in ultrasound images and an adaptation of the geodesic active contours technique for the segmentation of breast tumors. The anisotropic diffusion we propose is based on a texture description provided by a set of Gabor filters and allows reducing speckle noise while preserving edges. Furthermore, it is used to extract an initial pre-segmentation of breast tumors which is used as initialization for the active contours technique. This technique has been adapted to the characteristics of ultrasonography by adding certain texture-related terms which provide a better discrimination of the regions inside and outside the nodules. These terms allow obtaining a more accurate contour when the gradients are not high and uniform.

Rayleigh-Maximum-Likelihood Filtering for Speckle Reduction of Ultrasound Images

Speckle is a multiplicative noise that degrades ultrasound images. Recent advancements in ultrasound instrumentation and portable ultrasound devices necessitate the need for more robust despeckling techniques, for both routine clinical practice and teleconsultation. Methods previously proposed for speckle reduction suffer from two major limitations: 1) noise attenuation is not sufficient, especially in the smooth and background areas; 2) existing methods do not sufficiently preserve or enhance edges--they only inhibit smoothing near edges. In this paper, we propose a novel technique that is capable of reducing the speckle more effectively than previous methods and jointly enhancing the edge information, rather than just inhibiting smoothing. The proposed method utilizes the Rayleigh distribution to model the speckle and adopts the robust maximum-likelihood estimation approach. The resulting estimator is statistically analyzed through first and second moment derivations. A tuning parameter that naturally evolves in the estimation equation is analyzed, and an adaptive method utilizing the instantaneous coefficient of variation is proposed to adjust this parameter. To further tailor performance, a weighted version of the proposed estimator is introduced to exploit varying statistics of input samples. Finally, the proposed method is evaluated and compared to well-accepted methods through simulations utilizing synthetic and real ultrasound data.

The combined effect of spatial compounding and nonlinear filtering on the speckle reduction in ultrasound images

Recently, a spatial compounding ultrasound imaging method was presented that utilizes a conventional 64-element phased array transducer with two unfocused pistons, each placed at one of the sides of the phased array transducer. This method is augmented here by inclusion of nonlinear filtering of the compounded images. The combined effects of the specific spatial compounding and nonlinear filtering on speckle reduction in the generated ultrasound images are studied and evaluated in two stages: First, the image quality is studied when nonlinear filtering is used as part of the spatial compounding. The study is performed by simulations using the Field II program, by processing several B-mode images of a kidney. The second stage compares the results obtained by the simulations to those obtained by in vitro laboratory experiments. Five different compounding strategies and two nonlinear filters, Gaussian and anisotropic diffusion, are investigated and evaluated in terms of image quality parameters—contrast and signal-to-noise ratio. It is shown that the combination of “averaging + nonlinear Gaussian filtering” produces the greatest improvement of image quality. When compared to a conventional phased array imaging system, the spatial compounding method that includes the conventional 64-element phased array transducer with two unfocused pistons, and employs the “averaging + nonlinear Gaussian filtering” strategy, obtains improvement in SNR that has reached 334%. Thus, though this method necessitates a somewhat wider probe, it produces significantly improved images.

Control of variable structure elements in adaptive mathematical morphology for boundary enhancement of ultrasound images

AbstractThis paper discusses boundary enhancement function for adaptive morphology using variable structuring elements. The mechanism for boundary enhancement is quantitatively described. A method is proposed for setting the definition domain for the structuring elements and controlling their values, which is effective regarding boundary enhancement and speckle reduction in ultrasound images. It is shown that by controlling the value of the structuring element so that it is large near the boundary and small in other areas of the image, boundary enhancement and speckle elimination can be performed simultaneously, using the opening operation and closing operation. The spatial resolution and statistical properties of the speckle intensity in the ultrasound image are utilized to set these functions automatically on the basis of information on the object image. The effectiveness of the proposed method is demonstrated by a quantitative evaluation of a numerical phantom created in a computer simulation and in an application to boundary extraction from a real biological ultrasound image. It is shown that the performance of the proposed method in speckle reduction and boundary enhancement is better than that of the conventional method. © 2004 Wiley Periodicals, Inc. Electron Comm Jpn Pt 3, 87(11): 20–33, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ecjc.20117

Aggressive region growing for speckle reduction in ultrasound images

Speckle appears in all conventional medical B-mode ultrasonic images and can be an undesirable property since it may mask small but diagnostically significant features. In this paper, an adaptive filtering algorithm is proposed for speckle reduction. It selects a filtering region size using an appropriately estimated homogeneity value for region growth. Homogeneous regions are processed with an arithmetic mean filter. Edge pixels are filtered using a nonlinear median filter. The performance of the proposed technique is compared to two other methods––the adaptive weighted median filter and the homogeneous region growing mean filter. Results of processed images show that the method proposed reduces speckle noise and preserves edge details effectively.

Aggressive region growing filtering for speckle reduction in ultrasound images

Speckle noise is present in all conventional ultrasound images, and complicates the process of diagnosis as it can mask small but diagnostically significant features. Speckle reduction techniques can be applied prior to image formation [e.g., Chen et al., J. Ultrasound Imag. 18(2), 122–139 (1996)] or after image formation. Post-formation techniques can be implemented in software, whereas pre-formation techniques generally require hardware modifications. The approach described here is applied after image formation, and consists of two steps. In the first step, small ‘‘seed’’ regions are defined around each pixel in the image, and a homogeneity criterion is used to guide a procedure which identifies the maximal-size homogeneous region containing the pixel of interest. Once determined, this region is smoothed using a truncated arithmetic mean filter. Results on synthetic and real images demonstrate that this method preserves the sharpness of image edges yet reduces speckle noise, and compares well with weighted median filtering [Loupas et al., IEEE Trans. Circuits Syst. 236, 129–135 (1989)] and homogeneous region growing median filtering [Koo and Park, J. Ultrasound Imag. 13, 211–237 (1991)]. [Work supported by NSF and the Carl M. Hansen Foundation.]

Speckle reduction in ultrasound imaging

A system and a method for generating an ultrasound image of an interrogation region in an object with a transducer with a two-dimensional array of transducer elements, includes the steps of generating an ultrasound beam by activating many transducer elements of the two-dimensional array; electronically controlling the beam to illuminate substantially the same region from at least two orientations; capturing the echoes generated with the beam illuminating the object at different orientations; and analyzing the echoes from all directions to produce an image of the region of the object. The aperture of the transducer generating the beam is at least substantially equal to the aperture generated by a linear array of transducer elements extending across the substantially shortest distance between two opposite edges on the two-dimensional array. The ultrasound power emitted from the transducer elements is not spatially uniform, and the multiple echoes reduce speckle in the image.