A comparative evaluation of various de-speckling algorithms for medical images

Singh, Sonam; Jain, Akshat; Bhateja, Vikrant

doi:10.1145/2381716.2381724

Cited by 30 publications

(8 citation statements)

References 18 publications

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“…Performance of SRAD [18] degrades considerably as noise level rises whereas the proposed filter comfortably outperforms (In terms of CoC and PSNR) them at higher noise levels. For measuring speckle suppression, another specific metric is utilized known as Speckle Suppression Index (SSI) [1]. Lower value of SSI indicates that high filtering has been achieved on the speckled ultrasound images.…”

Section: Resultsmentioning

confidence: 99%

“…A comparative review of various works on despeckling of ultrasound images have been carried out by Loizou et al [29] focusing on images of carotid artery while of S. Singh et al [1] on uteral images. Both these reviews highlighted AD filtering as an appropriate technique for despeckling of ultrasound images.…”

Section: Proposed Despeckling Filtermentioning

confidence: 99%

“…The degree of effectiveness and accuracy of these procedures depends on the quality of the output medical images [1]. Mammography produces good results but with a serious limitation.…”

Section: Introductionmentioning

confidence: 99%

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Despeckling of ultrasound images using non-linear conductance function

Bhateja

Singh

Srivastava

et al. 2014

2014 International Conference on Signal Processing and Integrated Networks (SPIN)

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This paper presents a novel anisotropic diffusion (AD) filter for despeckling of ultrasound images using a non-linear conductance function. Proper choice of the conductance function while applying AD filters is extremely critical. This work proposes an improved conductance function that tends to suppress speckle with due preservation of diagnostic features. The diffusion coefficient of the AD filter thus decreases monotonically and acts as an edge seeking as well as preserving function. Peak Signal to Noise Ratio (PSNR), Coefficient of Correlation (CoC) and Speckle Suppression Index (SSI) are the quality metrics used for performance evaluation of the proposed despeckling filter.

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Section: Resultsmentioning

confidence: 99%

Section: Proposed Despeckling Filtermentioning

confidence: 99%

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Despeckling of ultrasound images using non-linear conductance function

Bhateja

Singh

Srivastava

et al. 2014

2014 International Conference on Signal Processing and Integrated Networks (SPIN)

Self Cite

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show abstract

“…Other moderations in the local statistics filtering were presented recently in the form of hybrid filters by V. Bhateja et al [22]. Sophisticated techniques for speckle suppression are categorized under Wavelet based and Anisotropic Diffusion based filtering techniques [18]- [20]. Speckle filtering techniques in either of these categories are able to provide satisfactory speckle suppression but with certain constraints.…”

Section: Literature Overview On Speckle Suppressionmentioning

confidence: 99%

“…Speckle reduction is needed for two main reasons: firstly to improve the human interpretation, or for visual enhancement and secondly, it forms mandatory pre-processing step for many image processing tasks. These algorithms are generally classified in three categories: Conventional spatial filtering, Multi-resolution filtering and Anisotropic Diffusion based filtering techniques [18]- [20]. A literature overview of the said categories of techniques along with a framework for present problem formulation is detailed in Section 2.…”

Section: Introductionmentioning

confidence: 99%