A theoretically simple and computationally efficient method to extract the midsagittal plane (MSP) from volumetric neuroimages is presented. The method works in two stages (coarse and fine) and is based on calculation of the Kullback and Leibler's (KL) measure, which characterizes the difference between two distributions. Slices along the sagittal direction are analyzed with respect to a reference slice to determine the coarse MSP. To calculate the final MSP, a local search algorithm is applied. The proposed method does not need any preprocessing, like reformatting, skull stripping, etc. The algorithm was validated quantitatively on 75 MRI datasets of different pulse sequences (T1WI, T2WI, FLAIR and SPGR) and MRA. The angular and distance errors between the calculated MSP and the ground truth lines marked by the expert were calculated. The average distance and angular deviation were 1.25 pixels and 0.63°, respectively. In addition, the algorithm was tested qualitatively on PD, FLAIR, MRA, and CT datasets. To analyze the robustness of the method against rotation, inhomogeneity and noise, the phantom data were used.