Performance Analysis of Speckle Reduction Filtering algorithms in B-Mode Ultrasound Images

Ratheesha, S; Beevi, A Shamla; Kalady, Saidalavi

doi:10.1109/incet51464.2021.9456191

Cited by 5 publications

(2 citation statements)

References 15 publications

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“…Frost filter effectively preserves edge characteristics and increases image clarity. This filter works in a way that reduces noise while maintaining image quality, but it may be less effective at dealing with high-frequency noise [16].…”

Section: Linear Speckle Reduction Filtersmentioning

confidence: 99%

Anisotropic Diffusion Method for Speckle Noise Reduction in Breast Ultrasound Images

2024

IJIES

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Breast ultrasound is an important technology for detecting breast lesions, but it faces a challenge in the form of speckle noise that negatively affects the quality of images. Effective methods are needed to eliminate this noise without compromising the image's fine edges and important features. In this work, we present a cutting-edge methodology based on a deep understanding of the dynamics of breast ultrasound images and the challenges of speckle noise. The method uses two separate stages of processing with two nonlinear filters. The first filter, the anisotropic diffusion filter, smooths out edges and boosts image contrast by lowering noise while keeping the tissue's structure. In the second stage, the SRAD filter is applied to remove residual noise and refine the image, increasing its clarity and improving the ability to visualize subtle lesions. This improved approach was evaluated using a comprehensive set of quantitative indices. The results confirmed the significant performance improvement provided, with the lowest MSE value of 0.2 and the highest PSNR of 59.3. Also, it reached the optimal value in the UQI and SSI, which indicates the robustness of the method in maintaining the quality of the structural image. The results confirm the value of the proposed approach and herald its promising potential for improving medical diagnostic results using breast ultrasound.

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Section: Linear Speckle Reduction Filtersmentioning

confidence: 99%

Anisotropic Diffusion Method for Speckle Noise Reduction in Breast Ultrasound Images

2024

IJIES

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“…Depending on other scatterers' positions, diffuse ultrasonic waves may undergo constructive or destructive interference (based on the wave phase), resulting in an increase or decrease in ultrasonic energy returning to the probe [31,32]. Several techniques have been proposed in the literature to reduce speckle noise without destroying important image information [33,34]. In this work, a speckle-reducing anisotropic diffusion (SRAD) filter, which is effective and has been successfully used in a previous work with similar images [35], has been adopted based on the following iterative formula [36]:…”

Section: Feature Extractionmentioning

confidence: 99%

3D Vascular Pattern Extraction from Grayscale Volumetric Ultrasound Images for Biometric Recognition Purposes

Iula

Vizzuso

2022

Applied Sciences

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Recognition systems based on palm veins are gaining increasing attention as they are highly distinctive and very hard to counterfeit. Most popular systems are based on infrared radiation; they have the merit to be contactless but can provide only 2D patterns. Conversely, 3D patterns can be achieved with Doppler or photoacoustic methods, but these approaches require too long of an acquisition time. In this work, a method for extracting 3D vascular patterns from conventional grayscale volumetric images of the human hand, which can be collected in a short time, is proposed for the first time. It is based on the detection of low-brightness areas in B-mode images. Centroids of these areas in successive B-mode images are then linked through a minimum distance criterion. Preliminary verification and identification results, carried out on a database previously established for extracting 3D palmprint features, demonstrated good recognition performances: EER = 2%, ROC AUC = 99.92%, and an identification rate of 100%. As further merit, 3D vein pattern features can be fused to 3D palmprint features to implement a costless multimodal recognition system.

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RETRACTED ARTICLE: Denoising transthoracic echocardiographic images in regional wall motion abnormality using deep learning techniques

Beevi,

Ratheesha,

Kalady

et al. 2023

Soft Comput

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Performance Analysis of Speckle Reduction Filtering algorithms in B-Mode Ultrasound Images

Cited by 5 publications

References 15 publications

Anisotropic Diffusion Method for Speckle Noise Reduction in Breast Ultrasound Images

Anisotropic Diffusion Method for Speckle Noise Reduction in Breast Ultrasound Images

3D Vascular Pattern Extraction from Grayscale Volumetric Ultrasound Images for Biometric Recognition Purposes

RETRACTED ARTICLE: Denoising transthoracic echocardiographic images in regional wall motion abnormality using deep learning techniques

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