Presents three-dimensional (3-D) reconstruction algorithms that address fully 3-D tomographic reconstruction for a septa-less, stationary, and rectangular camera. The field of view (FOV) encompasses the entire volume enclosed by detector modules capable of measuring depth of interaction (DOI). The filtered backprojection-based algorithms incorporate DOI, accommodate irregular sampling, and minimize interpolation the data by defining lines of response between the measured interaction points. The authors use fixed-width, evenly spaced radial bins order to use the fast Fourier transform but use irregular angular sampling to minimize the number of unnormalizable zero efficiency sinogram bins. To address persisting low-efficiency bins, the authors perform two-dimensional (2-D) nearest neighbor radial smoothing, employ a semi-iterative procedure to estimate the unsampled data, and mash the in plane and the first oblique projections to reconstruct the 2-D image the 3DRP algorithm. The authors present artifact-free, essentially spatially isotropic images of Monte Carlo data with full-width at half-maximum resolutions of 1.5, 2.3, and 3.1 mm at the center, the bulk, and the corners of the FOV, respectively.