Tomography defined as sensor fusion

Tomography is introduced as a sensing task, rather than a healthcare imaging application, best known for its embodiment in hospital scanners. Tomography sensing, imaging and data processing are summarized with emphasis on system phenomenology and design in relation with the inversion of measurement data. The main classification paradigms of sensor fusion are examined and the overlap with the theory and practice of computer (´hard-field´) tomography is shown in detail. It is demonstrated how concurrent fusion takes place when measuring path integrals; collaborative fusion - when defining a projection as a set of path integrals to allow data inversion from multiple projections, e.g. through the Fourier slice theorem; complementary fusion - when imaging the object in several auto-registered secondary contrasts. To cover the largest variety available, process tomography (i.e. non-medical tomography) case studies are examined in detail revealing the fusion tasks performed by various algorithms.