Photoacoustic (PA) computed tomography is based on the reconstruction of an internal PA source distribution from measurements acquired by scanning small-aperture ultrasound detectors over a surface that encloses the source under study [1]. The PA source is produced inside the object by the thermal expansion that results from a small temperature rise, which is caused by absorption of externally applied radiation of pulsed electromagnetic (EM) waves. This technique has great potential for application in the biomedical field because of the advantages of ultrasonic resolution in combination with EM absorption contrast. In general, different measurement geometries need different reconstruction algorithms (summarized in Ref. [1]). The three canonical geometries are planar, cylindrical, and spherical surfaces. In these algorithms, the acoustic property of the tissue is often assumed to be homogenous as the speed of sound in soft tissue is relatively constant at 1.5 mm/μs. The unique advantage of PA imaging is its ability to detect the inhomogeneous EM absorption property of tissues, even when the acoustic property is relatively homogeneous, whereas pure acoustic property differentiation should resort to conventional ultrasound imaging. In this chapter, we introduce a universal back-projection algorithm for the three common geometries [2,3].