Megavoltage cone-beam computed tomography (CBCT) using active matrix flat-panel imagers (AMFPIs) is a promising candidate for providing image guidance in radiation therapy. Unfortunately, the practical clinical implementation of this technique is limited by the relatively low detective quantum efficiency (DQE) of conventional megavoltage AMFPIs. This limitation is due to the modest thickness of the phosphor screen employed to convert incident x-rays to optical photons and the trade-off that exists between phosphor thickness and spatial resolution. Recently, our group has begun pursuing the development of thick crystalline segmented scintillating detectors as x-ray converters for AMFPIs so as to circumvent this limitation. In order to examine the potential of such detectors for providing soft-tissue visualization by means of CBCT at megavoltage energies, a Monte Carlo-based method was used to simulate the acquisition of projection images of a contrast phantom. These images were used to perform CT reconstructions by means of a Feldkamp-based algorithm. In this study, various detector configurations involving Csl and BGO scintillators at thicknesses of 10 mm and 40 mm were evaluated. In addition, since the simulations only considered energy deposition, and did not include optical phenomena, both segmented and non-segmented (continuous) detector configurations were evaluated. For the segmented CsI detectors, septal wall materials with densities lower, equivalent and higher than that of the scintillator were considered. Performance was quantified in terms of the contrast-to-noise ratio obtained for low-contrast, soft-tissue-equivalent objects (i.e., liver, brain, and breast) embedded in the phantom. The results obtained from these early studies suggest that such segmented converters can provide visualization of soft-tissue contrast in tomographic images at clinically practical doses. It is anticipated that the realization of optimized segmented detector designs will lead to clinically useful megavoltage AMFPIs exhibiting impressive performance.