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We consider the problem of aligning histological sections for 3D reconstruction and analysis. The method we propose is based on a block-matching strategy that allows us to compute local displacements between the sections. We then collect these local measures to estimate a rigid transformation. Our emphasis is on the necessity to use a robust approach for this estimation step. The process is integrated within a multi-scale scheme to improve both accuracy and computation time. We prove experimentally that we can reach sub-pixel accuracy and we show some results of aligning histological sections from a rat's brain and a rhesus monkey's brain.