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Updated: Jul 17, 2026

Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging
Published on: December 15, 2014
Development of ultrasound tomography for breast imaging: technical assessment
Nebojsa Duric1, Peter Littrup, Alex Babkin
1Karmanos Cancer Institute, 110 East Warren, Hudson-Weber Building, Suite 504, Detroit, Michigan 48201, USA. duric@karmanos.org
Abstract:
Ultrasound imaging is widely used in medicine because of its benign characteristics and real-time capabilities. Physics theory suggests that the application of tomographic techniques may allow ultrasound imaging to reach its full potential as a diagnostic tool allowing it to compete with other tomographic modalities such as x-ray computer tomography, and MRI. This paper describes the construction and use of a prototype tomographic scanner and reports on the feasibility of implementing tomographic theory in practice and the potential of ultrasound (US) tomography in diagnostic imaging. Data were collected with the prototype by scanning two types of phantoms and a cadaveric breast. A specialized suite of algorithms was developed and utilized to construct images of reflectivity and sound speed from the phantom data. The basic results can be summarized as follows. (i) A fast, clinically relevant US tomography scanner can be built using existing technology. (ii) The spatial resolution, deduced from images of reflectivity, is 0.4 mm. The demonstrated 10 cm depth-of-field is superior to that of conventional ultrasound and the image contrast is improved through the reduction of speckle noise and overall lowering of the noise floor. (iii) Images of acoustic properties such as sound speed suggest that it is possible to measure variations in the sound speed of 5 m/s. An apparent correlation with x-ray attenuation suggests that the sound speed can be used to discriminate between various types of soft tissue. (iv) Ultrasound tomography has the potential to improve diagnostic imaging in relation to breast cancer detection.
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