Frequency equalized compounding for effective speckle reduction in medical ultrasound imaging

Precision imaging—its impact on image quality and diagnostic confidence in breast ultrasound examinations

“…19 Although our VGA presented promising findings, no improvements in diagnostic efficacy were detected using ROC assessment. Whilst speckle reduction can increase the conspicuity of low-contrast lesions 12,20 and improve perception of subtle image details, 5,21 the absence of an effect of PI on performance in the present study is in line with the findings of Cha et al 8 In their studies using the alternate speckle reduction techniques of THI or spatial compounding, they did not show any significant improvement in the characterization of breast lesions. On the other hand, Su et al 6 did find increases in diagnostic accuracy when breast images were reprocessed by a speckle reduction algorithm based on a two-dimensional textural homogeneity histogram and directional averaging filters.…”

“…4 Optimal image quality is highly subjective, but, in general, operators and those who interpret images prefer low noise levels. 5 There are a number of factors that affect noise, a major one of these being subresolution scatter, which causes coherent interference of backscattered ultrasound signals. This results in a type of granular noise known as speckle, which degrades spatial and contrast resolution and reduces the detection of small, low-contrast targets of critical importance in breast imaging.…”

Gabor-based anisotropic diffusion for speckle noise reduction in medical ultrasonography

“…The SD FFSR is the standard deviation of the intensities at the FFSR, with a lower value indicating better speckle reduction. The CNR measures the contrast between the foreground and background, given by [2,17] CNR jμ 1 − μ 2 j∕ σ 2 1 σ 2 2 q ;…”

“…It is a form of locally correlated multiplicative noise caused by constructive and destructive coherent interferences of sound or light echoes from randomly distributed structure scatters, whose resolution is beyond imaging system capabilities [1,2]. In medical ultrasonography, the speckle noise obscures further image analysis, such as image segmentation, feature extraction and quantitative measurement, and thus reduces the accuracy of image interpretation and disease diagnosis.…”

“…Hardware-based techniques include polarization diversity, spatial compounding, frequency compounding, angular compounding, and strain compounding [2,[5][6][7]. These techniques achieve speckle reduction by averaging successive A-scans or B-scans, while attempting to preserve sample structural features.…”