Filtered backpropagation (FBPP) is a well-established reconstruction technique that is used in diffractive holographic tomography. The great advantage of the algorithm is the space-domain implementation, which enables avoiding the error-prone interpolation in the spectral domain that is an inherent part of the main counterpart of FBPP -the direct inversion tomographic reconstruction method. However, the fundamental flaw of FBPP is lack of generality, i.e. the method can be applied solely for the classical tomographic systems, where alternation of the measurement views is achieved by rotating a sample. At the same time, majority of the nowadays tomographic setups apply an alternative measurement concept, which is based on scanning of an illumination beam. The aim of this paper is to remove the mentioned limitation of the FBPP and enable its application in the systems utilizing scanning of illumination. This is achieved by introducing a new method of accounting for uneven cover of the sampled object frequencies, which applies normalization of the object spectrum with coherent transfer function of a considered tomographic system. The feasibility of the proposed, modified filtered backpropagation algorithm is demonstrated with numerical simulations, which mimic tomographic measurement of a complex sample, i.e. the Shepp-Logan phantom.