Measuring myofiber orientations from high-frequency ultrasound images using multiscale decompositions

• Type of Material: Article
• Authors: Xulei Qin, Emory University; Baowei Fei, Emory University
• Language: English
• Date: 2014-07-21
• Publisher: IOP Publishing: Hybrid Open Access
• Publication Version: Author Accepted Manuscript (After Peer Review)
• Copyright Statement: © 2014 Institute of Physics and Engineering in Medicine.
• Final Published Version (URL): http://dx.doi.org/10.1088/0031-9155/59/14/3907
• Title of Journal or Parent Work: Physics in Medicine and Biology
• ISSN: 0031-9155
• Volume: 59
• Issue: 14
• Start Page: 3907
• End Page: 3924
• Grant/Funding Information: This research is supported in part by NIH grants R01CA156775 and R21CA176684, Georgia Cancer Coalition Distinguished Clinicians and Scientists Award, and the Emory Molecular and Translational Imaging Center (NIH P50CA128301).
• Keywords: Engineering, Biomedical; CARDIAC MYOCYTES; myofiber orientation; Radiology, Nuclear Medicine & Medical Imaging; REDUCTION; SEGMENTATION; ultrasound imaging; RESOLUTION; Science & Technology; multiscale decomposition; SCALE-SPACE; MICRO-ULTRASOUND; Engineering; TRANSFORM; Life Sciences & Biomedicine; MUSCLE-CONTRACTION; Technology; ARCHITECTURE; ANISOTROPY
• Research Categories: Health Sciences, Radiology

Abstract

High-frequency ultrasound (HFU) has the ability to image both skeletal and cardiac muscles. The quantitative assessment of these myofiber orientations has a number of applications in both research and clinical examinations; however, difficulties arise due to the severe speckle noise contained in the HFU images. Thus, for the purpose of automatically measuring myofiber orientations from two-dimensional HFU images, we propose a two-step multiscale image decomposition method. It combines a nonlinear anisotropic diffusion filter and a coherence enhancing diffusion filter to extract myofibers. This method has been verified by ultrasound data from simulated phantoms, excised fiber phantoms, specimens of porcine hearts, and human skeletal muscles in vivo. The quantitative evaluations of both phantoms indicated that the myofiber measurements of our proposed method were more accurate than other methods. The myofiber orientations extracted from different layers of the porcine hearts matched the prediction of an established cardiac mode and demonstrated the feasibility of extracting cardiac myofiber orientations from HFU images ex vivo. Moreover, HFU also demonstrated the ability to measure myofiber orientations in vivo.