Small Aperture High-resolution Phased Array Ultrasound Imaging

Ultrasound imaging is widely used in medical diagnostic, industry detection andocean underwater detection etc. due to its individual characteristics such as noninvasive,low cost and high safety. The resolution of traditional ultrasound imaging is limited bythe wavelength and the aperture of the transducers array, which is hard to improve.Generally, the lateral resolution can be improved by increasing the aperture of thetransducers array. But the enlargement of the aperture is finite and the number of arraysin the units is limited in the actual system. The higher resolution of the image canprovide much more accurate information, so the demand of the resolution of ultrasoundimaging is more need. But the traditional ultrasound imaging method cannot achieve.In this paper, a new approach of ultrasound imaging method is presented, which isultrasound computational imaging. This method can obtain a higher resolutionultrasound image without enlarging the transducers’ aperture or increasing the numberof array in units. An new hot signal processing theory, Compressive Sensing (CS) isused in this method. Combining the spread and reflection characteristics of ultrasound,the high resolution ultrasound computing imaging model based on the CS isconstructed.In this paper, we first research the principle of the traditional phased arrayultrasound imaging (PAUI). Then, under the assumption that the detection scene issparse with respect to some bases or frames, the traditional phased array ultrasoundimaging can be converse into the reconstruction of detection scene. Further, thereconstruction problem can be solved and high resolution image is achieved.Finally, we design two kinds of experiments to test and verify our high resolutionimaging model.(1) Under the same aperture of transducers array conditions, our methodphased array ultrasound imaging based on CS (PAUI+CS) can achieve higher resolutioncompare to traditional phased array ultrasound imaging (PAUI). After a quantitativeanalysis of the image resolution, the experimental results show that the resolution of ourmethod can be achieved dozens of micron.(2) For the traditional method, keep theaperture and the number of arrays with the experiment one, and reduce the number ofarrays, meanwhile, maintain the aperture in our method, imaging the same detectionscene, our approach can obtain higher resolution than traditional method. Thesimulation shows the better performance of the proposed algorithm.