Image reconstruction for ultrasonic transmission tomography (UTT) is a complex problem. Due to the limited diffusion angle of ultrasonic transducers, few useful data are received from the opposite transducers so the image reconstruction problem is ill-posed. The traditional logic backprojection (LBP) algorithm cannot sufficiently deal with the sparse characteristic of measurement data. In this article, transducers with a large diffusion angle are designed to collect more information. A sparse preimaged orthogonal matching pursuit (SP-OMP) algorithm is presented for UTT image sparse reconstruction. The performance of the proposed algorithm is experimentally evaluated by a UTT system versus classical algorithms such as LBP, algebra reconstruction technique (ART), simultaneous iteration reconstruction (Sirt), Tikhonov, and L1-regularization. The quality parameters such as mean square error (MSE), position error (PE), size error (SE), relative error (RE), and correlation coefficient (CC) are surveyed which indicated that the SP-OMP algorithm could provide higher quality images than those provided by the conventional image reconstruction algorithms.