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Photoacoustic tomography : ウィキペディア英語版
Photoacoustic tomography

Photoacoustic tomography (PAT), or Photoacoustic computed tomography (PACT), is a materials analysis technique based on the reconstruction of an internal photoacoustic source distribution from measurements acquired by scanning ultrasound detectors over a surface that encloses the source under study.
==Introduction==
The PA source is produced inside the object by the thermal expansion that results from a small temperature rise, which is caused by the absorption of externally applied radiation of pulsed electromagnetic (EM) waves. This technique has great potential for applications in the biomedical field because of the advantages of ultrasonic resolution in combination with EM absorption contrast. PAT is also called optoacoustic tomography (OAT) or thermoacoustic tomography (TAT), with the term “thermoacoustic” emphasizing the thermal expansion mechanism in the PA generation. OAT refers particularly to light-induced PAT, while TAT is used to refer to rf-induced PAT.
Technically, each temporal PA signal, measured at various detection positions, provides one-dimensional radial information about the PA source relative to the detector position; 2D surface scans offer other 2D lateral information about the PA source. Combining the temporal and spatial measurements affords sufficient information for a complete reconstruction of a 3D PA source. Because the PA signal received by each ultrasound detector is the integral of the ultrasound waves over the sensing aperture of the detector, the reconstruction algorithms depend on the detector apertures as well as the scanning geometries. Small-aperture detectors are often used to approximate point detectors, which receive PA signals originating from spherical shells, centered at each point detector, with radii determined by the acoustic times of flight. The three geometries commonly used are planar, cylindrical, and spherical surfaces. Both Fourier- and time-domain reconstruction formulas with point-detector measurements for these geometries have been well established. Besides, algorithms based on other detection methods, such as large-aperture (plane), line, or circle detectors have also been derived.

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