Phase Insensitive Homomorphic Image Processing for Speckle Reduction

“…To compute the overall image noise factor, Chen et al [21,29] defined the pooled SNR as being that of a predefined set of homogeneous regions. It is calculated by:…”

Section: Evaluation Of Filtering Resultsmentioning

confidence: 99%

Segmentation of abdominal ultrasound images of the prostate using a priori information and an adapted noise filter

Betrouni

Vermandel

Pasquier

et al. 2005

Computerized Medical Imaging and Graphics

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“…The variable gain stages discussed in Section I-A were utilized to maximize the signal-to-noise ratio while avoiding the saturation of the A/D converters. The length of the (30) in [16]. This equation is:…”

Section: A Point Focusesmentioning

confidence: 99%

A Ring Transducer System for Medical

Waag

Fedewa

2006

IEEE Trans. Ultrason., Ferroelect., Freq. Contr.

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An ultrasonic ring transducer system has been developed for experimental studies of scattering and imaging. The transducer consists of 2048 rectangular elements with a 2.5-MHz center frequency, a 67% ;6 dB bandwidth, and a 0.23-mm pitch arranged in a 150-mm-diameter ring with a 25-mm elevation. At the center frequency, the element size is 0:30 42 and the pitch is 0.38 . The system has 128 parallel transmit channels, 16 parallel receive channels, a 2048:128 transmit multiplexer, a 2048:16 receive multiplexer, independently programmable transmit waveforms with 8-bit resolution, and receive amplifiers with time variable gain independently programmable over a 40-dB range. Receive signals are sampled at 20 MHz with 12-bit resolution. Arbitrary transmit and receive apertures can be synthesized. Calibration software minimizes system nonidealities caused by noncircularity of the ring and element-to-element response differences. Application software enables the system to be used by specification of high-level parameters in control files from which low-level hardware-dependent parameters are derived by specialized code. Use of the system is illustrated by producing focused and steered beams, synthesizing a spatially limited plane wave, measuring angular scattering, and forming b-scan images.

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“…post formation filtering methods. Under this class, many adaptive and fixed filters, such as L2-mean filter [13], nonlinear diffusion [14], adaptive weighted median filter (AWMF) [15], adaptive filter reduction (ASR) [12,16,18], and MAP [20] etc are developed.…”

Section: Literature Surveymentioning

confidence: 99%

“…The performance of the despeckling algorithms can be measured by image quality parameters as discussed in [16], [30], [31].…”

Section: Literature Surveymentioning

confidence: 99%

Reduction of speckle noise from medical images using principal component analysis image fusion

Kumar¹,

Bhadauria

Virmani

et al. 2014

2014 9th International Conference on Industrial and Information Systems (ICIIS)

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Images captured by different medical devices contain intrinsic artefacts, like ultrasound, CT, MRI images often contain speckle noise, which is the result of the destructive and constructive coherent summation of echoes. In these images, the speckle noise must be reduced cautiously as it also contains diagnostic information. Thus the despeckling algorithms should reduce speckle in homogeneous areas of the image and edges in the image should be preserved. In this paper a method to reduce the speckle noise is proposed which uses the concept of fusion. The performance of the proposed algorithm is quantified by calculating measures like MSE, SNR, PSNR and MSSI, which gives information about the extent of feature preservation and denoising.

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Phase Insensitive Homomorphic Image Processing for Speckle Reduction

Cited by 22 publications

References 24 publications

Segmentation of abdominal ultrasound images of the prostate using a priori information and an adapted noise filter

Segmentation of abdominal ultrasound images of the prostate using a priori information and an adapted noise filter

A Ring Transducer System for Medical

Reduction of speckle noise from medical images using principal component analysis image fusion

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