Lesion segmentation and bias correction in breast ultrasound B-mode images including elastography information

Gerard Pons; Joan Martí; Robert Martí; Mariano Cabezas; Andrew di Battista; J. Alison Noble

doi:10.1117/12.910591

14 February 2012 Lesion segmentation and bias correction in breast ultrasound B-mode images including elastography information

Gerard Pons, Joan Martí, Robert Martí, Mariano Cabezas, Andrew di Battista, J. Alison Noble

Author Affiliations +

Proceedings Volume 8314, Medical Imaging 2012: Image Processing; 83141E (2012) https://doi.org/10.1117/12.910591
Event: SPIE Medical Imaging, 2012, San Diego, California, United States

Abstract

Breast ultrasound (BUS) imaging is an imaging modality used for the detection and diagnosis of breast lesions and it has become a crucial modality nowadays specially for providing a complementary view when other modalities (i.e. mammography) are not conclusive. However, lesion detection in ultrasound images is still a challenging problem due to the presence of artifacts such as low contrast, speckle, inhomogeneities and shadowing. In order to deal with these problems and improve diagnosis accuracy, radiologists tend to complement ultrasound imaging with elastography data. Following the prominent relevance of elastography in clinical environments, it is reasonable to assume that lesion segmentation methods could also benefit from this complementary information. This paper proposes a novel breast ultrasound lesion segmentation framework for B-mode images including elastography information. A distortion field is estimated to restore the ideal image while simultaneously identifying regions of similar intensity inhomogeneity using a Markov Random Field (MRF) and a maximum a posteriori (MAP) formulation. Bivariate Gaussian distributions are used to model both B-mode and elastography information. This paper compares the fused B-mode and elastography framework with B-mode or elastography alone using different cases, including illustrative cases, where B-mode shows a well defined lesion and where elastography provides more meaningful information, showing a significant improvement when B-mode images are not conclusive which is often the case in non cystic lesions. Results show that combining both B-mode and elastography information in an unique framework makes the algorithm more robust and image quality independent.

Citation Download Citation

Gerard Pons, Joan Martí, Robert Martí, Mariano Cabezas, Andrew di Battista, and J. Alison Noble "Lesion segmentation and bias correction in breast ultrasound B-mode images including elastography information", Proc. SPIE 8314, Medical Imaging 2012: Image Processing, 83141E (14 February 2012); https://doi.org/10.1117/12.910591

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