Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Search research articles

Related Experiment Videos

Wavelet-based ultrasound image denoising: performance analysis and comparison.

F Yousefi Rizi¹, H Ahmadi Noubari, S K Setarehdan

¹Control and Intelligent Processing Center of Execellence, School of Electrical and Computer Eng, College of Engineering, University of Tehran, Tehran, Iran. f.yousefirizi@ece.u

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference

|January 19, 2012

Summary

Related Concept Videos

Imaging Studies II: Ultrasonography

Imaging Studies II: Ultrasonography

IntroductionUltrasonography, or renal ultrasound, is a noninvasive medical imaging technique that uses high-frequency sound waves to visualize the kidneys, ureters, bladder, and surrounding tissues.Indications for Urinary System UltrasonographyUrinary system ultrasonography is indicated in various clinical scenarios, such as:Kidney Stones (Urolithiasis): To detect and monitor the size and presence of kidney or urinary tract stones.Hydronephrosis: To assess the dilation of the renal pelvis and...

Assessing Blood pressure using a doppler ultrasound

Assessing Blood pressure using a doppler ultrasound

To obtain accurate blood pressure measurements in clinical settings, especially when traditional methods are insufficient, healthcare professionals utilize the Doppler ultrasound technique. This method uses high-frequency sound waves to detect blood flow within the arteries, which is crucial for patients with conditions that complicate circulatory system assessment.
Pre-Procedural Guidelines for Doppler Ultrasound Blood Pressure Assessment:
Preparation of Equipment:

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

A PCA/ICA based Fetal ECG Extraction from Mother Abdominal Recordings by Means of a Novel Data-driven Approach to Fetal ECG Quality Assessment.

Journal of biomedical physics & engineering·2017

Same author

A new approach for improving coronary plaque component analysis based on intravascular ultrasound images.

Ultrasound in medicine & biology·2010

Same author

An enhanced segmentation of blood vessels in retinal images using contourlet.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2009

See all related articles

This study compares wavelet-based methods for reducing speckle noise in ultrasound images. The curvelet technique proved most effective, significantly reducing noise while preserving important diagnostic features.

Area of Science:

Medical Imaging
Signal Processing
Biomedical Engineering

Background:

Ultrasound images suffer from multiplicative speckle noise due to coherent scattering.
Effective speckle noise filtering is crucial for accurate medical diagnosis.
Preserving diagnostic features during denoising is a key challenge.

Purpose of the Study:

To compare the performance of various wavelet-based denoising methods for ultrasound images.
To evaluate the efficacy of contourlet, curvelet, and different wavelet transforms in speckle noise reduction.
To identify the optimal method for preserving image quality and diagnostic information.

Main Methods:

Application of contourlet and curvelet techniques.
Utilized dual tree complex, real, and double density wavelet transform denoising methods.

Related Experiment Videos

Quantitative comparison of denoising results on real ultrasound images.

Main Results:

The curvelet-based method demonstrated superior performance in speckle noise reduction.
Other wavelet-based methods were also applied and compared.
The curvelet technique effectively minimized speckle noise content.

Conclusions:

Curvelet-based denoising is highly effective for ultrasound images.
This method significantly reduces speckle noise while preserving critical diagnostic features.
Wavelet-based techniques offer viable options for ultrasound image enhancement.