Although mammography is the gold standard for breast imaging, its limitations result in a high rate of biopsies of benign lesions and a significant false negative rate for women with dense breasts. In response to this imaging performance gap we have been developing a clinical breast imaging methodology based on the principles of ultrasound tomography. The Computed Ultrasound Risk Evaluation (CURE) system has been designed with the clinical goals of whole breast, operator-independent imaging, and differentiation of breast masses. This paper describes the first clinical prototype, summarizes our initial image reconstruction techniques, and presents phantom and preliminary in vivo results. In an initial assessment of its in vivo performance, we have examined 50 women with the CURE prototype and obtained the following results. (1) Tomographic imaging of breast architecture is demonstrated in both CURE modes of reflection and transmission imaging. (2) In-plane spatial resolution of 0.5 mm in reflection and 4 mm in transmission is achieved. (3) Masses > 15 mm in size are routinely detected. (4) Reflection, sound speed, and attenuation imaging of breast masses are demonstrated. These initial results indicate that operator-independent, whole-breast imaging and the detection of breast masses are feasible. Future studies will focus on improved detection and differentiation of masses in support of our long-term goal of increasing the specificity of breast exams, thereby reducing the number of biopsies of benign masses.
Accurate calibration is a requirement of many array signal processing techniques. We investigate the calibration of a transducer array using time delays. We derive a strategy based on the mean square error criterion and discuss how time delays that are not available can be interpolated from existing ones. The proposed method is made robust to noise and model mismatch by means of a novel iterative technique for distance matrix denoising. The convergence of the method is proved. Finally, the accuracy of the proposed calibration algorithm is assessed both in simulated scenarios and using experimental data obtained from an ultrasound scanner designed for breast cancer detection.
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