Literature DB >> 20639168

Large domain, low-contrast acoustic inverse scattering for ultrasound breast imaging.

Mark Haynes, Mahta Moghaddam.   

Abstract

We present a full-wave acoustic inverse scattering algorithm designed specifically for ultrasonic breast imaging. At ultrasonic frequencies, the image domain is roughly tens to hundreds of min cubed, where min is the smallest wavelength in the transmit signal spectrum. The expected range of contrasts for the breast imaging problem for density, compressibility, and compressive loss is ± 20% of the background. Because of the low contrast, Born iterations provide the basic structure of the inverse scattering algorithm. However, we use a multi-objective covariance-based least squares cost function in place of the basic least squares cost function to estimate the contrast functions. This cost function provides physically meaningful regularization based on a priori knowledge of the contrasts. Also, due to the size of the imaging domain and because the objects to be imaged are low contrast and inhomogeneous, we use the Neumann series solution as the forward solver. The largest domain imaged in simulation was 50 min x 50 min in 2D.

Mesh:

Year:  2010        PMID: 20639168     DOI: 10.1109/TBME.2010.2059023

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  4 in total

1.  Self-characterization of commercial ultrasound probes in transmission acoustic inverse scattering: transducer model and volume integral formulation.

Authors:  Mark Haynes; Sacha A M Verweij; Mahta Moghaddam; Paul L Carson
Journal:  IEEE Trans Ultrason Ferroelectr Freq Control       Date:  2014-03       Impact factor: 2.725

2.  Acoustic attenuation imaging of tissue bulk properties with a priori information.

Authors:  Fong Ming Hooi; Oliver Kripfgans; Paul L Carson
Journal:  J Acoust Soc Am       Date:  2016-09       Impact factor: 1.840

3.  Microwave breast imaging system prototype with integrated numerical characterization.

Authors:  Mark Haynes; John Stang; Mahta Moghaddam
Journal:  Int J Biomed Imaging       Date:  2012-03-08

4.  Enhancement of Multimodal Microwave-Ultrasound Breast Imaging Using a Deep-Learning Technique.

Authors:  Vahab Khoshdel; Ahmed Ashraf; Joe LoVetri
Journal:  Sensors (Basel)       Date:  2019-09-19       Impact factor: 3.576

  4 in total

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