Photoacoustic imaging (PAI) has the potential to acquire 3-D optical images at high speed. Attempts at 3-D photoacoustic imaging have used a dense 2-D array of ultrasound detectors or have densely scanned a single detector on a 2-D surface. The former approach is costly and complicated to realize, while the latter is inherently slow. We present a different approach based on a sparse 2-D array of detector elements and an iterative reconstruction algorithm. This approach has the potential for fast image acquisition, since no mechanical scanning is required, and for simple and compact construction due to the smaller number of detector elements. We obtained spatial sensitivity maps of the sparse array and used them to optimize the image reconstruction algorithm. We then validated the method on phantoms containing 3-D distributions of optically absorbing point sources. Reconstruction of the point sources from the time-domain signals resulted in images with good contrast and accurate localization (< or =1 mm error). Image acquisition time was 1 s. The results suggest that 3-D PAI with a sparse array of detector elements is a viable approach. Furthermore, the rapid acquisition speed indicates the possibility of high frame rate 3-D PAI.
Source localization by photoacoustic tomography is dependent on time-of-flight pressure data collected by one or more transducers at multiple positions about the imaged object. Errors in transducer position lead directly to errors in source localization. The objective of this work was to develop a method for experimental determination of transducer position for the purpose of (i) comparison of the measured to the expected transducer position, and (ii) automated calibration of transducer position in scanning and array setups. Our approach was to acquire the time of arrival data at each transducer using a small, point-like photoacoustic source from many locations in the imaged volume. Source placement was controlled with a 3D robotic gantry (accuracy ±0.01 mm). Time of arrival data for all source locations was used to compute a vector of source-transducer distances. The coordinates of each transducer location were then found by nonlinear parameter estimation for a function that related the source distance to the known source location and the unknown transducer location. Application of the method to a planar array of 14 transducers resulted in identification of the position of each element in the transducer array. This finding suggested that the method may be useful for (i) mapping transducer positions during validation and calibration studies, (ii) measuring the effective position of transducers that are asymmetric or have fabrication errors, and (iii) obtaining the mapping relationship between the imaging system and the imaging volume in situations where coregistration of image data from other modalities is desired.
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