Three-dimensional (2D) cell culture models have emerged as the basis for improved cell systems biology. However, there is a gap in robust computational techniques for segmentation of these model systems that are imaged through confocal or deconvolution microscopy. The main issues are the volume of data, overlapping subcellular compartments and variation in scale or size of subcompartments of interest, which lead to ambiguities for quantitative analysis on a cell-by-cell basis. We address these ambiguities through a series of geometric operations that constrain the problem through iterative voting and decomposition strategies. The main contributions of this paper are to (i) extend the previously developed 2D radial voting to an efficient 3D implementation, (ii) demonstrate application of iterative radial voting at multiple subcellular and molecular scales, and (iii) investigate application of the proposed technology to two endpoints between 2D and 3D cell culture models. These endpoints correspond to kinetics of DNA damage repair as measured by phosphorylation of γH2AX, and the loss of the membrane-bound E-cadherin protein as a result of ionizing radiation. Preliminary results indicate little difference in the kinetics of the DNA damage protein between 2D and 3D cell culture models; however, differences between membrane-bound E-cadherin are more pronounced.