Qin Xulei, Cong Zhibin, Jiang Rong, Shen Ming, Wagner Mary B, Kishbom Paul, Fei Baowei
Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA.
Department of Pediatrics, Emory University School of Medicine, Atlanta, GA.
Proc SPIE Int Soc Opt Eng. 2013 Mar 29;8675. doi: 10.1117/12.2006494.
Cardiac myofiber plays an important role in stress mechanism during heart beating periods. The orientation of myofibers decides the effects of the stress distribution and the whole heart deformation. It is important to image and quantitatively extract these orientations for understanding the cardiac physiological and pathological mechanism and for diagnosis of chronic diseases. Ultrasound has been wildly used in cardiac diagnosis because of its ability of performing dynamic and noninvasive imaging and because of its low cost. An extraction method is proposed to automatically detect the cardiac myofiber orientations from high frequency ultrasound images. First, heart walls containing myofibers are imaged by B-mode high frequency (>20 MHz) ultrasound imaging. Second, myofiber orientations are extracted from ultrasound images using the proposed method that combines a nonlinear anisotropic diffusion filter, Canny edge detector, Hough transform, and K-means clustering. This method is validated by the results of ultrasound data from phantoms and pig hearts.
心肌纤维在心脏跳动期间的应激机制中起着重要作用。肌纤维的取向决定了应力分布和整个心脏变形的效果。对这些取向进行成像和定量提取对于理解心脏生理和病理机制以及慢性病诊断至关重要。超声因其能够进行动态和无创成像且成本低,已广泛应用于心脏诊断。本文提出了一种从高频超声图像中自动检测心肌纤维取向的方法。首先,通过B型高频(>20 MHz)超声成像对含有肌纤维的心脏壁进行成像。其次,使用所提出的方法从超声图像中提取肌纤维取向,该方法结合了非线性各向异性扩散滤波器、Canny边缘检测器、霍夫变换和K均值聚类。该方法通过来自体模和猪心脏的超声数据结果进行了验证。