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This paper proposes a hidden Markov model (HMM) algorithm for 3D MRI brain segmentation using a hierarchical/multi-level parallel implementation. The new technique is implemented using standard message passing interface (MPI). Two platforms are used to test the proposed technique namely PC-cluster system and IBM Blue Gene (BG)/L system. On PC-cluster system, hierarchical-based parallel HMM algorithm achieves a twofold speedup on a three nodes cluster and a threefold speedup on a six nodes cluster. Communication overhead and data dependency nullify any speedup beyond six nodes. On IBM BG/L system, the high-speed communication network and optimised MPI allow more efficient processing nodes utilisation although the algorithm data dependency limits the net speedup achieved.