A probabilistic framework for ultrasound image decomposition

Igor V. Solovey; Oleg V. Michailovich; Robert S. Xu

doi:10.1117/12.844367

23 February 2010 A probabilistic framework for ultrasound image decomposition

Igor V. Solovey, Oleg V. Michailovich, Robert S. Xu

Proceedings Volume 7625, Medical Imaging 2010: Visualization, Image-Guided Procedures, and Modeling; 76252O (2010) https://doi.org/10.1117/12.844367
Event: SPIE Medical Imaging, 2010, San Diego, California, United States

Abstract

Image segmentation and tissue characterization are fundamental tasks of computer-aided diagnosis (CAD) in medical ultrasound imaging. As an initial step, such algorithms are usually based on extraction of pertinent features from the acquired ultrasound data. Typically, these features are computed directly from localized image segments, thereby representing local statistical properties of the image. However, the process of image formation of medical ultrasound suggests that such an approach could result in a variety of unwanted artifacts (such as excessively smooth segmentation boundaries or misclassification) at subsequent stages of the algorithm. In this work, we propose to first decompose the observed images into a number of their statistically distinct components. The decomposition is based on the maximum-a-posteriori (MAP) statistical framework which has been derived based on the signal and noise models appropriate for the ultrasound setting. Subsequently, each resulting component is used separately to extract a set of its corresponding features. When retrieved in this way (rather than directly from the observed image), the combined set of resulting features is shown to be capable of better discriminating between different tissue types. Examples of in silico simulations and in vivo experiments are provided to illustrate the practical usefulness of this technique for improving the results of ultrasound image segmentation.

Citation Download Citation

Igor V. Solovey, Oleg V. Michailovich, and Robert S. Xu "A probabilistic framework for ultrasound image decomposition", Proc. SPIE 7625, Medical Imaging 2010: Visualization, Image-Guided Procedures, and Modeling, 76252O (23 February 2010); https://doi.org/10.1117/12.844367

ACCESS THE FULL ARTICLE

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: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
10 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Image segmentation

Ultrasonography

Feature extraction

Tissues

Speckle

Image processing algorithms and systems

Electroluminescence

Show All Keywords

Keywords/Phrases

Search In:

Publication Years