Complex background suppression for vibro-acoustography images

• Published in: Ultrasonics Vol. 56; pp. 456 - 472
• Main Authors: Urban, Matthew W., Wang, Chenyi, Alizad, Azra, Fatemi, Mostafa
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier B.V 01.02.2015
• Subjects: Acoustic emission; Algorithms; Breast; Complex; Elasticity Imaging Techniques - methods; Filtering; Focal plane; Humans; Image contrast; Inclusions; Mathematics; Models, Theoretical; Parametric mixing; Phantoms, Imaging; Transducers; Ultrasonography, Mammary; Ultrasound; Vibro-acoustography; Acoustic emission; Vibro-acoustography; Ultrasound; Parametric mixing; Complex
• ISSN: 0041-624X; 1874-9968; 1874-9968
• DOI: 10.1016/j.ultras.2014.09.014

•Complex background suppression (CBS) uses the complex acoustic emission data.•CBS suppresses the background contribution of the images.•Images have enhanced contrast and better ability to separate object depth.•CBS was applied to sphere and breast phantom images and in vivo breast images.•The CBS method is a fast, linear approach to improve vibro-acoustography images. Vibro-acoustography (VA) is an ultrasound-based imaging modality that maps the acoustic response, or acoustic emission, of an object stimulated by two ultrasound waves at slightly different frequencies. VA images typically have a nonzero background intensity which can reduce contrast in images. We present a method that uses the complex representation of the acoustic emission data to estimate and suppress the unwanted background signal. This method utilizes a fast, linear approach to the problem called complex background suppression (CBS) using a square filtering window of size W×W. Images processed with the CBS algorithm have significantly enhanced contrast. Another improvement observed with this method is the ability to better localize objects within the depth direction with respect to the ultrasound transducer. This algorithm was tested on images obtained from scanning a phantom with spherical inclusions, a urethane breast phantom, and in vivo human breast. The results show that image quality is improved through processing with the CBS algorithm by increasing the contrast of features in the images. The contrast in the sphere phantom was increased by factors of 2–12 depending on the sphere. Utilizing the CBS algorithm increased the contrast in breast phantom by factors ranging from 1.1 to 5.4 for various inclusions. The size of the filtering window, W, affected the contrast achieved between the phantom features such as the spheres or simulated inclusions and the background material. Application of the CBS algorithm also demonstrated that objects could be localized in depth much better as the relationship to image intensity level was directly correlated to objects located at the center of the focal plane in the axial direction. This method has wide applicability for all VA imaging applications.