Characteristic matching-based adaptive fast bilateral filter for ultrasound speckle reduction

Shao, Dangguo; Liu, Paul; Dong, Cheng-Di

doi:10.1016/j.patrec.2012.12.006

Cited by 11 publications

(9 citation statements)

References 14 publications

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“…The performance measure that has been used to evaluate the ultrasound image enhancement method is the despeckle values. The sample measurement techniques of the enhancement quality are the signal-to-noise ratio (SNR) [6] [7,9], the Mean preservation and Variance reduction [10], the ultrasound de-speckling assessment index ( Q  ) The signal-to-noise (SNR) value [9], the Speckle index (SI). These are the performance measurements of the smooth speckle noise.…”

Section: Measurementsmentioning

confidence: 99%

“…These are the performance measurements of the smooth speckle noise. The quality of the edge structure of ultrasound images is measured by the Pratt's Figure of merit (PFOM) [6,10] [8],  [7] and  [16].…”

Section: Measurementsmentioning

confidence: 99%

“…The performance of the proposed EBDU method is evaluated between the original liver ultrasound image and the enhanced liver ultrasound image. The EBDU is compared to Shao [6], Coupé [26], and Yu [10] in four methods utilizing real liver ultrasound images. In addition, the Slope-Smooth Speckle Index (SLSI), Equivalent number of looks (ENL), Speckle suppression index (SSI), and accuracy of segmentation the PDF region by the CADPDF system [27] are the efficiency metric of all enhancement methods.…”

Section: Enhancment Performance Evaluationmentioning

confidence: 99%

“…The ultrasound image enhancement methods have been developed using filters which were based on time and frequency domains. The filters that have been developed based on the time domain are Shao [6], Wong [7], Zhang [8], Coup'e [9], and Yu [10]. The mentioned filters have been developed by applying the bilateral filtering, Monte Calo filter, Fuzzy subpixel, NL-means filter, Blockwise technique, respectively.…”

Section: Introductionmentioning

confidence: 99%

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Enhancement of Bile Duct Ultrasound Images for Cholangiocarcinoma Surveillance

Wayalun

Saiyod

Chamadol

2018

MJCS

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Bile Ducts Cancer (Cholangiocarcinoma: CCA) is a serious public health problem. The surgical resection is one of the curative treatments for CCA. The surgical resection in the early stage of the CCA gives a good chance for recovery; therefore, early detection in the surgical resection stage is of a critical importance. Periductal fibrosis (PDF) in the bile duct is one factor which is considered about CCA in Thailand. It can be detected using the liver ultrasound images; however, the liver ultrasound images contain speckle noise which decreases PDF detection performance. This paper proposes a new method for enhancement of bile duct ultrasound image (EBDU). The main idea of the EBDU method is to reduce the speckle noise and enhance clear structures of the liver ultrasound images. The proposed method consists of three processes which are the speckle reduction, edge preservation, and intraregion smoothing. The speckle reduction is performed in frequency domain to filter out the high frequency and low frequency noise out of the ultrasound image by using the bandpass filter. The criterion of the bandpass filter is the size of the structures in the ultrasound image, which could be large structures (mirrored edges) and small structures (smoothing). Edge preservation is then performed by applying the statistics filter to distinctly increase the boundary structure; it sorts out all pixel values from the surrounding neighborhood into a numerical order. Finally, intraregions of the liver ultrasound images are smoothed by intra-region smoothing process which can diffuse the homogeneous region. The enhanced liver ultrasound images were tested by computer-aided detection on PDF regions (CADPDF). Variety of liver ultrasound images were used. To evaluate and compare the performance of the proposed method, four measurements are applied which are the scan line pixel (SLP), the Slope-Smooth Speckle Index (SLSI), Equivalent number of looks (ENL), Speckle suppression index (SSI), and the accuracy achieved through the PDF regions segmentation. The experimental results show that the proposed method is able to give higher success rate of enhancing liver ultrasound images compared to other methods. Moreover, the accuracy of CADPDF system was evaluated. The proposed EBDU method and other methods are applied in CADPDF system. The experimental results show that the proposed EBDU method achieved better performance than other methods, giving an accuracy of 80.36%.

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Section: Measurementsmentioning

confidence: 99%

Section: Measurementsmentioning

confidence: 99%

Section: Enhancment Performance Evaluationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Enhancement of Bile Duct Ultrasound Images for Cholangiocarcinoma Surveillance

Wayalun

Saiyod

Chamadol

2018

MJCS

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“…A disadvantage of this filter is the difficulty to define the values of its parameters and of the number of iterations for the efficient processing of a particular class of input image. An excessive number of iterations, for example, may cause undue loss of image information affecting the quality of possible further processing results, such as segmentation and classification of the structures [Shao et al, 2013]. Anisotropic diffusion-based filters have shown promise in smoothing medical images, but the noise model involved in the input images must be accurately defined, which is very difficult for ultrasound images due to the great variability and non-linearity of the noise involved.…”

mentioning

confidence: 99%

Smoothing of ultrasound images using a new selective average filter

Araujo

Constantinou

Tavares

2016

Expert Systems with Applications

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Ultrasound images are strongly affected by speckle noise making visual and computational analysis of the structures more difficult. Usually, the interference caused by this kind of noise reduces the efficiency of extraction and interpretation of the structural features of interest. In order to overcome this problem, a new method of selective smoothing based on average filtering and the radiation intensity of the image pixels is proposed. The main idea of this new method is to identify the pixels belonging to the borders of the structures of interest in the image, and then apply a reduced smoothing to these pixels, whilst applying more intense smoothing to the remaining pixels.Experimental tests were conducted using synthetic ultrasound images with speckle noisy added and real ultrasound images from the female pelvic cavity. The new smoothing method is able to perform selective smoothing in the input images, enhancing the transitions between the different structures presented. The results achieved are promising, as the evaluation analysis performed shows that the developed method is more efficient in removing speckle noise from the ultrasound images compared to other current methods. This improvement is because it is able to adapt the filtering process according to the image contents, thus avoiding the loss of any relevant structural features in the input images.

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