Contrast enhancement and segmentation of ultrasound images: a statistical method

Guofang Xiao; J. Michael Brady; Alison J. Noble; Yongyue Zhang

doi:10.1117/12.387616

6 June 2000 Contrast enhancement and segmentation of ultrasound images: a statistical method

Guofang Xiao, J. Michael Brady, Alison J. Noble, Yongyue Zhang

Proceedings Volume 3979, Medical Imaging 2000: Image Processing; (2000) https://doi.org/10.1117/12.387616
Event: Medical Imaging 2000, 2000, San Diego, CA, United States

Abstract

Ultrasound B-scan images often exhibit intensity inhomogeneities caused by non-uniform beam attenuation within the body. These cause major problems for image analysis, both by manual and computer-aided techniques, particularly the computation of quantitative measurements. We present a statistical model that exploits knowledge of tissue properties and intensity inhomogeneities in ultrasound for simultaneous contrast enhancement and image segmentation. The underlying model was originally proposed for correction of the B₁ bias field distortion and segmentation of magnetic resonance (MR) images. A physics-based model of intensity inhomogeneities in ultrasound images shows that the bias field correction method is well suited to ultrasound B-scan images. The tissue class labeling and the intensity correction field are estimated using the maximum a posteriori (MAP) principle, in an iterative, multi-resolution manner. The algorithm has been applied to breast and cardiac ultrasound images. The results demonstrate that it can successfully remove intensity inhomogeneities caused by varying attenuation as well as uninteresting intensity changes of background tissues. With the removal of intensity inhomogeneities, significant improvement is achieved in tissue contrast and segmentation result.

Citation Download Citation

Guofang Xiao, J. Michael Brady, Alison J. Noble, and Yongyue Zhang "Contrast enhancement and segmentation of ultrasound images: a statistical method", Proc. SPIE 3979, Medical Imaging 2000: Image Processing, (6 June 2000); https://doi.org/10.1117/12.387616

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