To better convey key comparative information at a glance, we designed a novel approach to derive simplified geometric representations from primary 3D datasets. This collection of algorithms can computationally order data, such as cell organelles, segmented in 3D from tomograms, into functionally relevant and visually comprehensible 3D diagrams that retain accurate basic morphometric parameters (e.g. number of compartments, cellular dimensions, membrane surface area and/or volume, etc.). The algorithms organize the intertwined 3D surface-contour data into simplified orthogonal cell abstractions and the components can be sorted to emphasize particular comparisons with proximity. The resulting representation allows both expert and non-specialist viewers to rapidly compare cell and/or phenotypic parameters at a glance, thus providing a powerful tool for rapidly assessing and communicating key functional insights and quantitative differences in one object or between multiple objects.