A parallelizable real-time motion tracking algorithm with applications to ultrasonic strain imaging

• Published in: Physics in medicine & biology Vol. 52; no. 13; pp. 3773 - 3790
• Main Authors: Jiang, J, Hall, T J
• Format: Journal Article
• Language: English
• Published: England IOP Publishing 07.07.2007
• Subjects: Algorithms; Breast - pathology; Breast Neoplasms - diagnostic imaging; Breast Neoplasms - pathology; Contrast Media - chemistry; Elasticity; Humans; Models, Theoretical; Radiographic Image Interpretation, Computer-Assisted - instrumentation; Reproducibility of Results; Software; Thyroid Gland - diagnostic imaging; Thyroid Gland - pathology; Thyroid Neoplasms - diagnostic imaging; Thyroid Neoplasms - pathology; Time Factors; Ultrasonics; Ultrasonography - instrumentation; Ultrasonography - methods
• ISSN: 0031-9155; 1361-6560
• DOI: 10.1088/0031-9155/52/13/008

Ultrasound-based mechanical strain imaging systems utilize signals from conventional diagnostic ultrasound systems to image tissue elasticity contrast that provides new diagnostically valuable information. Previous works (Hall et al 2003 Ultrasound Med. Biol. 29 427, Zhu and Hall 2002 Ultrason. Imaging 24 161) demonstrated that uniaxial deformation with minimal elevation motion is preferred for breast strain imaging and real-time strain image feedback to operators is important to accomplish this goal. The work reported here enhances the real-time speckle tracking algorithm with two significant modifications. One fundamental change is that the proposed algorithm is a column-based algorithm (a column is defined by a line of data parallel to the ultrasound beam direction, i.e. an A-line), as opposed to a row-based algorithm (a row is defined by a line of data perpendicular to the ultrasound beam direction). Then, displacement estimates from its adjacent columns provide good guidance for motion tracking in a significantly reduced search region to reduce computational cost. Consequently, the process of displacement estimation can be naturally split into at least two separated tasks, computed in parallel, propagating outward from the center of the region of interest (ROI). The proposed algorithm has been implemented and optimized in a Windows system as a stand-alone ANSI C++ program. Results of preliminary tests, using numerical and tissue-mimicking phantoms, and in vivo tissue data, suggest that high contrast strain images can be consistently obtained with frame rates (10 frames s(-1)) that exceed our previous methods.