In this paper, a novel decoder for underdetermined MIMO systems with low decoding complexity is proposed. The development of the proposed decoder consists of two stages. First, an improved slab decoding algorithm efficiently obtains all valid candidate points within a given slab. Next, a multi-slab based decoding algorithm finds the optimal solution by conducting intersections on the obtained candidate set with dynamic radius adaptation. The proposed decoder offers the advantages of low computational complexity and near-ML decoding performance for underdetermined MIMO systems. Simulation results indicate that it effectively reduces the complexity as compared to existing decoders, especially for large antenna numbers and/or constellations.