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Calculating and visualizing the sound field of transducers is a key task in the development of most ultrasound applications. In most cases it is sufficient to calculate the directivity pattern or a plane slice of the sound field using the point source synthesis method. To date no freeware tool is available which is able to simulate the sound field for arbitrary rectangular transducer array matrices for different excitation signals. The developed ”Transducer Array Calculation GUI” (TAC) includes phase- and frequency-informations as well as apodization to calculate sound fields of various transducer configurations. TAC also offers to include the medium attenuation and transducer's electrical impedance characteristics. Our software supports fast and realistic transducer engineering and it is open source.

We designed and built a 3D ultrasound computer tomography (USCT) device with a nearly isotropic and spatially invariant 3D point spread function, to be tested in a clinical study. The objective of this work was to image two healthy volunteers and to evaluate the USCT volumes in comparison to corresponding Magnetic Resonance Images (MRI). The here presented volumes are reflectivity images generated with 3D synthetic aperture focusing technique. The volunteers were imaged with different parameterizations of the data acquisition. The data acquisition time was between four and twelve minutes. For both volunteers we found that the breast surface and inner structures are clearly shown in the USCT volume and fit the structures given by the MRI.

Ultrasound Computer Tomography (USCT) is an upcoming modality for early breast cancer diagnosis, which provides morphological as well as quantitative imaging. In order to compare USCT images to the standard modality X-ray mammography, a 2D/3D registration has to be applied. To analyze the relevance of sound speed images as a quantitative imaging method for tissue characterization, the aim of this paper is to quantify sound speed values of different types of tissue using mammograms as ground truth. Mammograms are segmented and classified into fat, glandular and tumorous tissue. For each tissue class the average sound speed in the registered sound speed image is calculated. The mean absolute sound speed was 1457 m/s for regions segmented as fatty tissue, 1470 m/s for glandular and 1509 m/s for tumorous tissue. For all ten datasets, the sound speed in tumorous tissue was significantly higher than in glandular and fatty tissue. Also glandular and fatty tissue could be separated easily by the absolute sound speed values. By color-coding sound speed, quantitative information from USCT and morphological information from X-ray mammography are fused for combined diagnosis. We believe this method will help radiologists in gaining experience in the reading of USCT images. The combination of diagnostic information is likely to be beneficial to early breast cancer detection.