Deformation correction in ultrasound imaging in an elastography framework

Tissue deformation in ultrasound imaging is an inevitable phenomenon and poses challenges to the development of many techniques related to ultrasound image registration, including multimodal image fusion, freehand three-dimensional ultrasound, and quantitative measurement of tissue geometry. In this thesis, a novel trajectory-based method to correct tissue deformation in ultrasound B-mode imaging and elastography is developed in the framework of elastography. To characterize the change of tissue deformation with contact force, a force sensor is used to provide contact force measurement. Correlation-based displacement estimation techniques are applied to ultrasound images acquired under different contact forces. Based on the estimation results, a two-dimensional trajectory field is constructed, where pixel coordinates in each scan are plotted against the corresponding contact force. Interpolation or extrapolation by polynomial curve fitting is then applied to each trajectory to estimate the image under a specified contact force. The performance of displacement estimation and polynomial curve fitting are analyzed in a simulation framework incorporating FEM and ultrasound simulation. Influences of parameter selection are also examined. It is found that in displacement estimation, the coarse-to-fine approach outperforms single-level template search, and correlation filtering in coarse scale provides noticeable improvement in estimation performance. The strategies of image acquisition and order selection in polynomial curve fitting are also evaluated. Additionally, a finer force resolution is found to give better performance in predicting pixel positions under zero force. Deformation correction in both B-mode imaging and elastography is demonstrated through simulation and in-vitro experiments. The performance of correction is quantified by translational offset and area estimation of the tissue inclusions. It is found that, for both B-mode and elastography images, those performance metrics are significantly improved after correction. Moreover, it is shown that a finer resolution in force control gives better performance in deformation correction, which agrees with the analysis of polynomial curve fitting.

Department dc:contributor.department

Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2010

Author dc:creator

• Sun, Shih-Yu

Advisor dc:contributor.advisor

• Brian W. Anthony.

• Electrical Engineering and Computer Science.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/62483

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/62483