Development and Characterization of a Superresolution Ultrasonic Transducer.

Highly sensitive ultrasound probes are needed to expand the capabilities of biomedical ultrasound and industrial nondestructive testing (NDT). Pursuing better imaging quality, while keeping fabrication costs low, is an important trend in the current development of ultrasound imaging systems. In this article, we report the development and characterization of an ultrasonic transducer that (super)focuses ultrasonic waves beyond the so-called diffraction limit, that is, the beamwaist is roughly narrower than one wavelength. The transducer comprises an additive manufactured case with a circular flat piezoelectric actuator fixed at the bottom and a core-shell lens (with a stainless steel core and a polymer shell) placed at the probe's conical tip. The core-shell lens is responsible to superfocusing effect of ultrasonic waves. Operating at approximately 3 MHz, the transverse and axial resolution for C- and B-scan images are, respectively, 0.65λ and 3λ/2 , with the wavelength being [Formula: see text]. The system depth-of-field is 6.3λ . To demonstrate the transducer capability to resolve subwavelength structures, we successfully obtain images of a copper wire forming a Y-intersection, whose branches a diameter similar to human hair ( [Formula: see text]). Our results represent a solid step toward the development of ultrasonic superresolution transducer applied for biomedical imaging and shallow NDT of materials.

Photoacoustic-based thermal image formation and optimization using an evolutionary genetic algorithm

Abstract Introduction For improved efficiency and security in heat application during hyperthermia, it is important to monitor tissue temperature during treatments. Photoacoustic (PA) pressure wave amplitude has a temperature dependence given by the Gruenesein parameter. Consequently, changes in PA signal amplitude carry information about temperature variation in tissue. Therefore, PA has been proposed as an imaging technique to monitor temperature during hyperthermia. However, no studies have compared the performance of different algorithms to generate PA-based thermal images. Methods Here, four methods to estimate variations in PA signal amplitude for thermal image formation were investigated: peak-to-peak, integral of the modulus, autocorrelation of the maximum value, and energy of the signal. Changes in PA signal amplitude were evaluated using a 1-D window moving across the entire image. PA images were acquired for temperatures ranging from 36oC to 41oC using a phantom immersed in a temperature controlled thermal bath. Results The results demonstrated that imaging processing parameters and methods involved in tracking variations in PA signal amplitude drastically affected the sensitivity and accuracy of thermal images formation. The sensitivity fluctuated more than 20% across the different methods and parameters used. After optimizing the parameters to generate the thermal images using an evolutionary genetic algorithm (GA), the percentage of pixels within the acceptable error was improved, in average, by 7.5%. Conclusion Optimization of processing parameters using GA could increase the accuracy of measurement for this experimental setup and improve quality of PA-based thermal images.