In the planning process of Leksell Gamma Knife brain radiosurgery a treatment planning system is used for the calculation and optimization of the absorbed dose. The most commonly used algorithm in Leksell Gamma Plan treatment planning (LGP, Elekta AB, Stockholm, Sweden) system is the TMR 10 algorithm (Elekta AB, Stockholm, Sweden), based on the tissue maximum ratio. It assumes tissue-water equivalency along with the homogeneity of tissue composition and density. Near heterogeneous structures, the dose delivered to the target volume and the dose calculated by the TMR 10 Algorithm can differ significantly. The convolution algorithm is available alongside the TMR 10 algorithm. It convolves functions describing the energy transfer between the primary photon beam and the secondary electrons with functions describing how that energy is further distributed in tissue. That way it accounts for the differences between tissues. This study aimed to verify the convolution algorithm’s accuracy for simple mono-isocentric dose distributions of Leksell Gamma Knife under the assumption that it might perform more accurately than the TMR 10 algorithm in the absorbed dose calculation. The detectors used were the GAFChromic EBT3 radiochromic film (Ashland Advanced Materials, Bridgewater, New Jersey, USA), the Semiflex TM31010 and the PinPoint3D TM31022 cylindrical ionization chambers (PTW, Freiburg, Germany) and the Diode E silicon detector (PTW, Freiburg, Germany). The results of this study do not support the hypothesis that the convolution algorithm performs better than the TMR 10 algorithm in calculation of the absorbed dose for the mid-brain locations of interest. The TMR 10 algorithm performs within 2.1% or less relative to the experimental values, yielding more accurate results than the convolution algorithm for most measurement points, which differ up to 3.1%. The convolution algorithm systematically underestimated the absorbed dose. All output factors and dose profiles calculated with both algorithms were in excellent agreement with reference values.