Ms. Devyani Bedekar Profile

Devyani Bedekar

at Cleveland Clinic

SPIE Involvement:

Author

Publications (1)

This will count as one of your downloads.

You will have access to both the presentation and article (if available).

DOWNLOAD NOW

This content is available for download via your institution's subscription. To access this item, please sign in to your personal account.

Email or Username Forgot your username?

Password Forgot your password?

Show

Keep me signed in

No SPIE account? Create an account

Proceedings Article | 12 April 2005 Paper

Choosing the optimal mother wavelet for decomposition of radio-frequency intravascular ultrasound data for characterization of atherosclerotic plaque lesions

Devyani Bedekar, Anuja Nair, D. Geoffrey Vince

Proceedings Volume 5750, (2005) https://doi.org/10.1117/12.595616

KEYWORDS: Wavelets, Intravascular ultrasound, Image information entropy, Tissues, Statistical analysis, Algorithm development, Data acquisition, Biological research, Fourier transforms, Signal analyzers

Read Abstract +

Aim: The objective of this work is to determine the optimal basis function to perform wavelet analysis for tissue characterization of radio frequency intravascular ultrasound (IVUS) backscattered data. This is the most important step in wavelet analysis as it ensures accurate decomposition of the original signal into the various frequency bands. The criterion to choose the mother wavelet that is best suited to the data depends on the intended application. Wavelet families possessing properties like orthogonality, regularity, stability and admissibility have previously been shown to have application in tissue characterization. Algorithm: Depending on the usable data bandwidth known from previous studies we decomposed data using a 4-level decomposition scheme. We then calculated Shannon’s entropy for every level and employed “minimum Shannon entropy criterion” to determine the best mother wavelet for signal decomposition. According to this criterion, accurate decomposition is indicated when the total entropy of the daughter (decomposed) levels is lower than the entropy of the parent level. Analysis and Results: We acquired 40 MHz IVUS data ex-vivo from 10 left anterior descending (LAD) coronary arteries. Data was acquired such that each frame comprised of 256 scanlines. Next, we randomly selected 3 scanlines for each LAD and applied the above-mentioned Shannon entropy criterion for these 30 scanlines. We analyzed 23 mother wavelets from different families. Daubechies 3rd order wavelet accurately decomposes 29/30 scanlines at all levels. Daubechies 6th order wavelet appears optimal for 21/30 scanlines. Future direction: To obtain more precise signal decomposition, the optimal mother wavelet should be selected at every decomposition level. The best mother wavelet is indicated by the lowest Shannon entropy for that particular level.

My Library

You currently do not have any folders to save your paper to! Create a new folder below.

Folder Name

Folder Description

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks. You are receiving this notice because your organization may not have SPIE eBooks access.*

*Shibboleth/Open Athens users─please sign in to access your institution's subscriptions.

To obtain this item, you may purchase the complete book in print or electronic format on SPIE.org.

ORGANIZATIONAL
Sign in with credentials provided by your organization.

Organizational Username

Organizational Password

Show/Hide Password

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members:

Non-members: ADD TO CART

Keywords/Phrases

Search In:

Publication Years