Performance analysis of a regularized algorithm for elasticity imaging

Claire Pellot-Barakat, Jie Liu, Frederique Frouin, Alain Herment, Michael F. Insana

Research output: Contribution to journalConference articlepeer-review

Abstract

We investigated image quality features of a regularized optical flow (ROF) algorithm for strain imaging - noise, contrast and spatial resolution. ROF image features were compared to those obtained using a standard multi-resolution cross-correlation (MRCC) algorithm under equivalent conditions. Comparisons were made quantitatively using resolution phantom data and qualitatively using in vivo breast and flow phantom data. With a small applied compression, the axial resolution limit (ARL), peak strain value and standard deviation of the noise (SON) for strain measured at the layer were respectively 1.78 lp/mm, 0.52%, 0.04% (ROF) and 1.78 lp/mm, 0.52%, 0.54% (MRCC). With a large compression, the ARL, strain and SDN were respectively 2 lp/mm, 3.15% and 0.29% (ROF) and 2 lp/mm, 3.08% and 1.05% (MRCC). These results show that the ROF algorithm provides up to an order of magnitude reduction in image noise with comparable contrast and spatial resolution. Flow phantoms with a large dynamic range for stiffness also showed that ROF effectively eliminates decorrelation noise without a significant reduction in contrast or resolution.

Original languageEnglish (US)
Pages (from-to)1622-1625
Number of pages4
JournalProceedings of the IEEE Ultrasonics Symposium
Volume2
StatePublished - 2003
Externally publishedYes
Event2003 IEEE Ultrasonics Symposium - Proceedings - Honolulu, HI, United States
Duration: Oct 5 2003Oct 8 2003

ASJC Scopus subject areas

  • Acoustics and Ultrasonics

Fingerprint

Dive into the research topics of 'Performance analysis of a regularized algorithm for elasticity imaging'. Together they form a unique fingerprint.

Cite this