In this work we use a massively parallel architecture for solving the problem of reconstructing human brain sections from experimental data obtained from a Gamma camera equipped with parallel-hole collimators. We compute least-squares regularized solutions by means of weighted conjugate gradient iterations coupled with a suitable stopping rule. The computations are distributed to the CRAY T3E parallel processors following two different decomposition strategies obtaining high speed up values. This decomposition strategy can be easily extended to a wide family of iterative reconstruction algebraic methods.