Weight for it… adaptive beamformers in passive acoustic mapping for cavitation imaging
As the applications of therapeutic ultrasound expand across neurological, oncological and musculoskeletal medicine, monitoring of cavitation activity offers the potential for non-invasive treatment guidance and optimization of safety and efficacy. When implemented with a distributed set of sensors,...
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          | Published in | The Journal of the Acoustical Society of America Vol. 148; no. 4; p. 2449 | 
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| Main Authors | , , , , , , , , | 
| Format | Journal Article | 
| Language | English | 
| Published | 
          
        01.10.2020
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| Online Access | Get full text | 
| ISSN | 0001-4966 1520-8524  | 
| DOI | 10.1121/1.5146758 | 
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| Summary: | As the applications of therapeutic ultrasound expand across neurological, oncological and musculoskeletal medicine, monitoring of cavitation activity offers the potential for non-invasive treatment guidance and optimization of safety and efficacy. When implemented with a distributed set of sensors, simple delay and sum beamformers can be effective for cavitation source detection, but localization and quantification capabilities may be hindered when using conventional diagnostic ultrasound arrays. More generally, when observations of the emitted field are limited by the quantity, bandwidth, and geometric distribution of the receivers employed, and/or are subject to uncertainties in array calibration and signal propagation path, â~robust' data-adaptive beamformers can offer considerable improvements in the estimation of emission source properties. This paper reviews the concepts of adaptive beamformers—wherein outputs are calculated using data-dependent receiver weights—and their application to cavitation monitoring. Examples are presented for two such beamformers used in our laboratory, demonstrating their enhanced imaging capabilities, their relative computational cost, and the physical interpretation of their optimized weights. Finally, we discuss clinical translation of these techniques, critical factors in quantitative data interpretation, and how beamformed data can be used to estimate and correct for in vivo propagation effects. | 
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| ISSN: | 0001-4966 1520-8524  | 
| DOI: | 10.1121/1.5146758 |