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Reconstructing 3D distributions from their 2D projections is a ubiquitousproblem in various scientific fields, particularly so in observationalastronomy. In this work, we present a new approach to solving this problem: aVienna inverse-Abel-transform based object reconstruction algorithm AVIATOR.The reconstruction that it performs is based on the assumption that thedistribution along the line of sight is similar to the distribution in theplane of projection, which requires a morphological analysis of the structuresin the projected image. The output of the AVIATOR algorithm is an estimate ofthe 3D distribution in the form of a reconstruction volume that is calculatedwithout the problematic requirements that commonly occur in otherreconstruction methods such as symmetry in the plane of projection or modellingof radial profiles. We demonstrate the robustness of the technique to differentgeometries, density profiles, and noise by applying the AVIATOR algorithm toseveral model objects. In addition, the algorithm is applied to real data: Wereconstruct the density and temperature distributions of two dense molecularcloud cores and find that they are in excellent agreement with profilesreported in the literature. The AVIATOR algorithm is thus capable ofreconstructing 3D distributions of physical quantities consistently using anintuitive set of assumptions.

AVIATOR: Morphological object reconstruction in 3D. An application to dense cores