There are several simulators for medical ultrasound (US) applications that can fully compute the nonlinear propagation on the transmitted pulse and the corresponding radio-frequency (RF) images. Creanuis is one recent model used to generate nonlinear RF images; however, the time requirements are long compared with linear models using a convolution strategy. In this paper, we describe an approach using convolution coupled with nonlinear information to create a pseudoacoustic tool that is able to quickly generate realistic US images. Several point-spread functions (PSFs) are computed with Creanuis. These PSFs are extracted at different depths in order to take into account variation in the resolution and apparition of harmonics during propagation. One convolution is then conducted for each PSF to generate a set of nonlinear raw RF images. The final image is obtained by merging these raw images using a PSF-weighting function. This hybrid Creanuis strategy was extended to 2-D, 2-D +t , 3-D, and 3-D +t images for both linear and phased-array geometries. We validated h-Creanuis using the mean deviation between the proposed images and those created using Creanuis and examined their statistical distributions. The mean deviations of Creanuis and h-Creanuis are below 2.5% for fundamental and second-harmonic images. The 3-D +t images obtained demonstrate the correct motion characteristics for speckle in sequences of both fundamental and second-harmonic images.