An adaptive weighted median filter for speckle suppression in medical ultrasonic images

Loupas, T.; McDicken, W.N.; Allan, Paul L.

doi:10.1109/31.16577

Cited by 637 publications

(328 citation statements)

References 16 publications

Supporting

Mentioning

317

Contrasting

Unclassified

Order By: Relevance

“…The main disadvantage of the median filter is the extra computation time needed to sort the intensity value of the each set. The adaptive weighted median [10] is a median filter through the introduction of weight coefficients and consequently the smoothing characteristics of the filter according to the local statistics around each pixel of the image. The more emphasis is placed on the central weights, the ability of the weighted median to suppress noise decreases but also the increases signal preservation.…”

Section: B Median Filtermentioning

confidence: 99%

A Review on Analysis of Speckle reduction in Ultra Sound Images

Bhat¹

2018

IJRASET

View full text Add to dashboard Cite

Ultrasound is an inexpensive and widely used imaging modality for the diagnosis and staging of a number of diseases. In the past two decades, it has benefited from major advances in technology and has become an indispensable imaging modality, due to its flexibility and non-invasive character. Ultrasound imaging utilizes high-frequency sound waves to picture inner structures by contrasting reflection signals created when a light emission is anticipated into the body and ricochets back at interfaces between the structures. However the convenience of ultrasound imaging is corrupted by the nearness of flag dependant noise known as dot (speckle). The speckle pattern depends on the structure of the image tissue and various imaging parameters. Speckle noise show in ultrasound picture influences edges and fine subtle elements which constrain the differentiation determination and make symptomatic more troublesome. There are two main purposes for speckle reduction in medical ultrasound imaging (i) To improve the human interpretation of ultrasound images (ii) De-speckling is the preprocessing step for many ultrasound image processing tasks such as segmentation and registration. Various strategies have been proposed for decrease speckle noise in ultrasound imaging. The objective of this paper is to give an overview of speckle noise reduction in ultrasound imaging. Keywords: Speckle noise, Ultrasound image, Different methods, filters analysis I. INTRODUCTIONUltrasound imaging assumes pivotal part in therapeutic imaging because of its non-obtrusive nature, ease and capacity of framing ongoing imaging. Medical Ultrasound imaging is done using ultrasonic waves in 3 to 20 MHz range. Ultrasound waves are created from the transducer and go through body tissues and when the wave achieves a protest or surface with various surface or acoustic in nature, it is reflected back. These echoes are received by the apparatus (the transducer array) and converted into electric current. These signals are amplified, conditioned and shown on a display device in real time. The image generated using Ultrasound imaging commonly known as Ultrasound Scanning is called an Ultra sonogram. The resolution of the image will be better by using higher frequencies but at the same time limits the depth of the penetration. There are diverse methods of ultrasound imaging.The most common modes are (a) B-mode -the basic two-dimensional intensity mode, (b) M-mode to assess moving body parts (e.g. cardiac movements) from the echoed sound and (c) Color mode pseudo coloring based on the detected cell motion. Ultrasound imaging is a generally utilized and safe restorative indicative system, because of its non intrusive nature, minimal effort and capacity of framing ongoing imaging. To accomplish the most ideal determination it is vital that medicinal pictures be sharp, clear and free of commotion and ancient rarities. However event of spot noise is an issue with ultrasound imaging. Spot is the curio caused by impedance of vitality from haphazardly appropriate...

show abstract

Section: B Median Filtermentioning

confidence: 99%

A Review on Analysis of Speckle reduction in Ultra Sound Images

Bhat¹

2018

IJRASET

View full text Add to dashboard Cite

show abstract

“…In [2] the image is filtered by convolving with a 3X3 Gaussian low pass filter followed by thresholding and to eliminate the noise morphological dilation and erosion have been applied. Adaptive weighted median filter (AWMF) for reducing speckle noise in ultrasound images is presented in [3] which is based on the weighted median. By adjusting the weight coefficients and consequently the smoothing characteristics of the filter according to the local statistics around each point of the image, it is possible to suppress noise while edges and other important features are preserved.…”

Section: Related Workmentioning

confidence: 99%

Analysis for Diagnosing Myocardial Ischemia by Detecting the Boundary of Left Ventricle in Echocardiography Sequences using GVF snake

Sameena¹,

Shanavas²

2014

IOSRJCE

View full text Add to dashboard Cite

show abstract

“…Based on the Bayesian non-local means filter [46] and on the Speckle noise model introduced in [54], the authors propose a non-local filter for ultrasound images that uses the so-called Pearson distance for computing patch similarity:…”

Section: Extension To Other Distance Measuresmentioning

confidence: 99%

Generalised Nonlocal Image Smoothing

Pizarro

Pavel²,

Didas

et al. 2010

Int J Comput Vis

View full text Add to dashboard Cite

We propose a discrete variational approach for image smoothing consisting of nonlocal data and smoothness contraints that penalise general dissimilarity measures defined on image patches. One of such dissimilarity measures is the weighted 2 distance between patches. In such a case we derive an iterative neighbourhood filter that induces a new similarity measure in the photometric domain. It can be regarded as an extended patch similarity measure that evaluates not only the patch similarity of two chosen pixels, but also the similarity of their corresponding neighbours. This leads to a more robust smoothing process since the pixels selected for averaging are more coherent with the local image structure. The suggested approach includes two recently proposed filters as special cases: The NLmeans filter of Buades et al. and the NDS filter of Mrázek et al. In fact, the approach introduced here can be considered as a generalisation of the latter filter. We evaluate our method for the task of denoising greyscale and colour images degraded by Gaussian and impulse noise, demonstrating that it compares very well to other more sophisticated patch-based approaches.

show abstract

An adaptive weighted median filter for speckle suppression in medical ultrasonic images

Cited by 637 publications

References 16 publications

A Review on Analysis of Speckle reduction in Ultra Sound Images

A Review on Analysis of Speckle reduction in Ultra Sound Images

Analysis for Diagnosing Myocardial Ischemia by Detecting the Boundary of Left Ventricle in Echocardiography Sequences using GVF snake

Generalised Nonlocal Image Smoothing

Contact Info

Product

Resources

About