An adaptive speckle suppression filter based on Nakagami distribution

Ghofrani, Sedigheh; Jahed‐Motlagh, Mohammad Reza; Ayatollahi, Ahmad

doi:10.1109/eurcon.2001.937769

Cited by 23 publications

(27 citation statements)

References 10 publications

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“…The appearance of Nakagami Model in the context of US images has already been noticed in [26] to design a speckle suppression filter in spatial domain. By assuming equal probability of negative and positive speckle wavelet coefficients, the twosided Nakagami distribution is used for approximating the speckle component.…”

Section: Modelling Of Speckle Wavelet Coefficientsmentioning

confidence: 97%

Homomorphic wavelet thresholding technique for denoising medical ultrasound images

Gupta

Chauhan

Saxena

2005

Journal of Medical Engineering & Technology

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A novel homomorphic wavelet thresholding technique for reducing speckle noise in medical ultrasound images is presented. First, we show that the speckle wavelet coefficients in the logarithmically transformed ultrasound images are best described by the Nakagami family of distributions. By exploiting this speckle model and the Laplacian signal prior, a closed form, data-driven, and spatially adaptive threshold is derived in the Bayesian framework. The spatial adaptivity allows the additional information of the image (such as identification of homogeneous or heterogeneous regions) to be incorporated into the algorithm. Further, the threshold has been extended to the redundant wavelet representation, which yields better results than the decimated wavelet transform. Experimental results demonstrate the improved performance of the proposed method over other well-known speckle reduction filters. The application of the proposed method to a realistic US test image shows that the new technique, named HomoGenThresh, outperforms the best wavelet-based denoising method reported in [1] by more than 1.6 dB, Lee filter by 3.6 dB, Kaun filter by 3.1 dB and band-adaptive soft thresholding [2] by 2.1 dB at an input signal-to-noise ratio (SNR) of 13.6 dB.

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Section: Modelling Of Speckle Wavelet Coefficientsmentioning

confidence: 97%

Homomorphic wavelet thresholding technique for denoising medical ultrasound images

Gupta

Chauhan

Saxena

2005

Journal of Medical Engineering & Technology

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“…Among these density functions, the Nakagami and K-distribution provides better overall statistical fit to the observed data over a broad range of scattering conditions [22]. Due to analytical simplicity, the Nakagami distribution has been used extensively by many researchers in US image processing applications [22,23]. The density function of the speckle under the Nakagami model can be expressed as…”

Section: Speckle Statisticsmentioning

confidence: 98%

A versatile technique for visual enhancement of medical ultrasound images

Gupta

Kaur

Chauhan

et al. 2007

Digital Signal Processing

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“…The received RF echo signal has high dynamic range of around 80dB, hence non linear compression technique is necessary to reduce the dynamic range but it will change *This work is supported by IIT Hyderabad under 'IU-ATC' project 1 This paper focuses on performance evaluation of various compression techniques for ultrasound imaging system that can be used to scan the patients in rural areas and transmit the images to the cloud using handheld ultrasound system developed by IIT Hyderabad as shown in Fig .1.…”

Section: Introductionmentioning

confidence: 99%

“…The Radio Frequency (RF) signal is modeled as Nakagami distribution [1] to study the characteristics of tissue. In [2] the authors could characterize the tissue based on nakagami model and speckle pattern as characterization depends on the part of tissue called parenchyma, that differentiates between various tissue compositions [3].…”

Section: Introductionmentioning

confidence: 99%

Compression techniques for IoT enabled handheld ultrasound imaging system

Akkala

Ramesh

Rajalakshmi

et al. 2014

2014 IEEE Conference on Biomedical Engineering and Sciences (IECBES)

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Received echo signals of transducer in ultrasound imaging have a high dynamic range of 12 bits and hence cannot be displayed on Cathode Ray Tube (CRT), Liquid Crystal Display (LCD) monitors of ultrasound machine. Log compression is being used to compress the data to 8 bits. Since log compression is a non linear compression it is very difficult to trace the original characteristics of the signal. In this paper various global and local compression techniques were studied as a replacement for log compression so that the dynamic range of image can be retrieved if the physician has a better monitor for display, and also ensure minimum error in the retrieved signal leading to minimum error in retrieved image. From the results it is observed that Structural SIMilarity (SSIM) of wavelet compressed image is 1.02 times more and that of gamma compressed image is 2.24 times more than log compressed image. Gamma based compression can be preferred to log and wavelet based compression, as it gives good quality image when compared with other compression techniques, but cannot be used to retrieve the statistical properties when expanded, since these statistical properties are helpful for doctors for better analysis. Wavelet based compression serves this purpose and hence is best suited for Internet of Things (IoT) enabled ultrasound system for remote diagnosis in the cloud.

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An adaptive speckle suppression filter based on Nakagami distribution

Cited by 23 publications

References 10 publications

Homomorphic wavelet thresholding technique for denoising medical ultrasound images

Homomorphic wavelet thresholding technique for denoising medical ultrasound images

A versatile technique for visual enhancement of medical ultrasound images

Compression techniques for IoT enabled handheld ultrasound imaging system

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