Chedsada Chinrungrueng

Fast edge-preserving noise reduction for ultrasound images

Edge-preserving noise reduction is an essential operation for computer-aided ultrasound image processing and understanding. This paper describes a novel filter which is a two-dimensional extension of the one-dimensional Savitzky-Golay filter. The new filter, referred to as the two-dimensional weighted Savitzky-Golay filter, is based on the least squares polynomial surface fitting to image intensities. The performance of the proposed filter has been compared with that of the commonly used median filter in reducing speckle noise in ultrasound images. Experimental results indicate that the new filter can achieve, at least, the same level of noise reduction and edge preservation as that of the median filter, but with far less computation rims. Since its complexity scales linearly with the problem size, the new filter is suitable for filtering problems with large windows. In addition, it also shows to be less sensitive to the size of the filtering window compared to the median filter.

Reconstruction of 3D ultrasound images based on Cyclic Regularized Savitzky–Golay filters

This paper presents a new three-dimensional (3D) ultrasound reconstruction algorithm for generation of 3D images from a series of two-dimensional (2D) B-scans acquired in the mechanical linear scanning framework. Unlike most existing 3D ultrasound reconstruction algorithms, which have been developed and evaluated in the freehand scanning framework, the new algorithm has been designed to capitalize the regularity pattern of the mechanical linear scanning, where all the B-scan slices are precisely parallel and evenly spaced. The new reconstruction algorithm, referred to as the Cyclic Regularized Savitzky-Golay (CRSG) filter, is a new variant of the Savitzky-Golay (SG) smoothing filter. The CRSG filter has been improved upon the original SG filter in two respects: First, the cyclic indicator function has been incorporated into the least square cost function to enable the CRSG filter to approximate nonuniformly spaced data of the unobserved image intensities contained in unfilled voxels and reduce speckle noise of the observed image intensities contained in filled voxels. Second, the regularization function has been augmented to the least squares cost function as a mechanism to balance between the degree of speckle reduction and the degree of detail preservation. The CRSG filter has been evaluated and compared with the Voxel Nearest-Neighbor (VNN) interpolation post-processed by the Adaptive Speckle Reduction (ASR) filter, the VNN interpolation post-processed by the Adaptive Weighted Median (AWM) filter, the Distance-Weighted (DW) interpolation, and the Adaptive Distance-Weighted (ADW) interpolation, on reconstructing a synthetic 3D spherical image and a clinical 3D carotid artery bifurcation in the mechanical linear scanning framework. This preliminary evaluation indicates that the CRSG filter is more effective in both speckle reduction and geometric reconstruction of 3D ultrasound images than the other methods.

Combining Savitzky-Golay filters and median filters for reducing speckle noise in SAR images

This paper describes a new filter developed for reducing speckle noise in SAR images. The new filter, referred to as the Savitzky-Golay median hybrid filter, is a two-dimensional extension of the one-dimensional FIR-median hybrid filter. It operates by performing a series of two-dimensional polynomial least squares fitting, and defines its output as the median of the results obtained from such least squares fits. The polynomial least squares fitting performed in the new filter is efficiently implemented based on the simplified procedure developed in the Savitzky-Golay filter. The performance of the proposed filter is compared with that of the median filter, the Lee filter, and the Frost filter in reducing speckle noise of a synthetic image and of a real synthetic aperture radar (SAR) image.

Real-Time Speckle Reduction of Ultrasound Images Based on Regularized Savitzky-Golay Filters

This paper describes a new filtering algorithm developed for real-time speckle reduction of ultrasound medical images. The new filter, referred to as the Regularized Savitzky-Golay filter, is the two-dimensional Savitzky-Golay filter, enhanced with a mechanism for adapting the degree of smoothing to match the strength of speckle. The results comparing the new filter algorithm with Adaptive Speckle Reduction and Adaptive Weighted Median filters on a synthetic test pattern and an ultrasound cyst image are reported.

Comparative evaluation of adaptive filters in motion artifact cancellation for pulse oximetry

Among non-invasive approaches, pulse oximeters are most commonly used medical equipment for measuring blood oxygen saturation level. However, their accuracy is severely subjected to motion artifact and environmental noise. In this paper, we aim to evaluate empirically the effectiveness of adaptive filters in motion artifact cancellation for finger pulse oximeters. Our experiments compared the Least Mean Square (LMS) adaptive filter and the Exponentially Weighted Least Square (EWLS) adaptive filter with the Minimum Correlation Discrete Saturation Transform (MCDST). The experimental results indicate that both adaptive filters can perform better than the MCDST, and the EWLS adaptive filter better than the LMS adaptive filter in motion noise reduction.

Real-time speckle reduction and coherence enhancement of ultrasound images based on anisotropic Savitzky-Golay filters

This paper describes a new filtering algorithm developed for real-time speckle reduction and coherence enhancement of ultrasound images. The new filter, referred to as the anisotropic Savitzky-Golay filter, is the two-dimensional, weighted Savitzky-Golay filter enhanced with a mechanism for adjusting both the degree and direction of the smoothing so that they both match the anisotropic properties of each local regions in the image. The results comparing the new filter with adaptive speckle reduction and adaptive weighted median filters on a synthetic test pattern and an ultrasound thyroid image are also reported.

Comparative and evaluative the adaptive filter in motion artifact cancellation of pulse oximetry

The problem of blood oxygen calculation is calculation when the patient has some motion. The methods for increase the accuracy in calculation are proposed by many researchers. In this paper, we proposed the experiment to consider the efficiency between the method we study. In this paper, we consider two methods, first is the adaptive filter and second is minimum correlation discrete saturation transform (MCDST). From the adaptive filter, we consider two different methods for find the motion artifact, Exponentially Weighted Least Square (EWLS), Least Mean Square (LMS). The result from the experiment can summarize that the adaptive filter algorithm has the higher efficiency than the minimum correlation discrete saturation transform (MCDST). The result from the experiment also summarize that Exponentially Weighted Least Square (EWLS) has the better property for reduce motion artifact from pulse oximeter signal than Least Mean Square (LMS).

A design of LMS with order adaptation for feedback echo cancellation in hearing aids

This paper describes a design of a hybrid adaptive filter for feedback echo cancellation in hearing aids. The proposed design utilizes a multiplexing direct form (MDF) FIR filter, and the LMS algorithm with order adaptation in order to reduce a requirement of a chip area and to minimize power consumption wasted in activities of non active taps. The proposed design can operate up to 6.25MS/s, and could save 26% of power consumption compared to a conventional fixed order FIR filter with LMS adaptation.

Reconstruction of three-dimensional ultrasound images based on cyclic Savitzky-Golay filters

We present a new algorithm for reconstructing a three-dimensional (3-D) ultrasound image from a series of two-dimensional B-scan ultrasound slices acquired in the mechanical linear scanning framework. Unlike most existing 3-D ultrasound reconstruction algorithms, which have been developed and evaluated in the freehand scanning framework, the new algorithm has been designed to capitalize the regularity pattern of the mechanical linear scanning, where all the B-scan slices are precisely parallel and evenly spaced. The new reconstruction algorithm, referred to as the cyclic Savitzky-Golay (CSG) reconstruction filter, is an improvement on the original Savitzky-Golay filter in two respects: First, it is extended to accept a 3-D array of data as the filter input instead of a one-dimensional data sequence. Second, it incorporates the cyclic indicator function in its least-squares objective function so that the CSG algorithm can simultaneously perform both smoothing and interpolating tasks. The performance of the CSG reconstruction filter compared to that of most existing reconstruction algorithms in generating a 3-D synthetic test image and a clinical 3-D carotid artery bifurcation in the mechanical linear scanning framework are also reported.

Multiscale adaptive regularisation Savitzky–Golay method for speckle noise reduction in ultrasound images

Speckle noise is one of the major artefacts in ultrasound images. The denoising faces the trade-off between noise suppression and structural preservation. In this study, multiscale adaptive regularisation Savitzky-Golay (MARSG) method, the new filter for removing speckle noise, is proposed. The proposed method combines the benefit of the multiscale analysis and the outstanding noise removing capability of Savitzky-Golay (SG) filter. The Laplacian pyramid is employed to separate an image into the noise, texture and object layers. Adaptive regularisation Savitzky-Golay (ARSG) filter is developed as the denoising filter in the noise and the texture layers. The denoising of the ARSG filter is adaptively adjusted in order to preserve the edges of objects in the image. The experiments on the synthetic and ultrasound images demonstrated that MARSG method offered better balance between noise removal and structural preservation than non-linear multiscale wavelet diffusion, feature-enhanced speckle reduction and regularised SG filter.