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Since the introduction of standard techniques for isosurface extraction from volumetric datasets, one of the hardest problems has been to reduce the number of triangles (or polygons) generated.This paper presents an algorithm that considerably reduces the number of polygons generated by a Marching Cubes-like scheme without excessively increasing the overall computational complexity. The algorithm assumes discretization of the dataset space and replaces cell edge interpolation by midpoint selection. Under these assumptions, the extracted surfaces are composed of polygons lying within a finite number of incidences, thus allowing simple merging of the output facets into large coplanar polygons.An experimental evaluation of the proposed approach on datasets related to biomedical imaging and chemical modelling is reported.