Pre-envelope deconvolution for increased lesion detection efficiency in ultrasonic imaging

Craig K. Abbey; Roger J. Zemp; Michael F. Insana

doi:10.1117/12.480099

22 May 2003 Pre-envelope deconvolution for increased lesion detection efficiency in ultrasonic imaging

Craig K. Abbey, Roger J. Zemp, Michael F. Insana

Author Affiliations +

Proceedings Volume 5034, Medical Imaging 2003: Image Perception, Observer Performance, and Technology Assessment; (2003) https://doi.org/10.1117/12.480099
Event: Medical Imaging 2003, 2003, San Diego, California, United States

Abstract

We use an ideal observer model to evaluate the efficiency of human observers detecting a simulated lesion in the presence of speckle, and the ability of pre-envelope deconvolution to improve performance in this task. We model the lesion as a localized area of increased scatter density, which translates into an area of higher variance in the ultrasound signal. Assuming the scattering function and electronic noise obey Gaussian distributions, the ideal observer for lesion detection is given by a quadratic function of the in-phase (I) and quadrature (Q) data. For comparison, human-observer performance is assessed through two-alternative forced-choice (2AFC) psychophysical studies after making a B-mode image by computing the magnitude (envelope) of the I and Q components. We also consider the effect of removing spatial correlations in the I and Q components, before computing the magnitude (pre-envelope deconvolution). Our Psychophysical studies indicate approximately a 4-fold improvement in detection efficiency with pre-envelope deconvolution.

Citation Download Citation

Craig K. Abbey, Roger J. Zemp, and Michael F. Insana "Pre-envelope deconvolution for increased lesion detection efficiency in ultrasonic imaging", Proc. SPIE 5034, Medical Imaging 2003: Image Perception, Observer Performance, and Technology Assessment, (22 May 2003); https://doi.org/10.1117/12.480099

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