Three-dimensional (3D) tissue culture provides a physiologically relevant microenvironment for distinguishing malignant from non-malignant breast cell phenotypes. 3D culture assays can also be used to test novel cancer therapies and predict a differential response to radiation between normal and malignant cells in vivo. However, biological measurements in such complex models are difficult to quantify and current approaches do not allow for in-depth multifaceted assessment of individual colonies or unique sub-populations within the entire culture. This is in part due to the limitations of imaging at a range of depths in 3D culture resulting from optical aberrations and intensity attenuation. Here, we address these limitations by combining sample smearing techniques with high-throughput 2D imaging algorithms to accurately and rapidly quantify imaging features acquired from 3D cultures. Multiple high resolution imaging features especially designed to characterize 3D cultures show that non-malignant human breast cells surviving large doses of ionizing radiation acquire a "swelled acinar" phenotype with fewer and larger nuclei, loss of cell connectivity and diffused basement membrane. When integrating these imaging features into hierarchical clustering classification, we could also identify subpopulations of phenotypes from individual human tumor colonies treated with ionizing radiation or/and integrin inhibitors. Such tools have therefore the potential to further characterize cell culture populations after cancer treatment and identify novel phenotypes of resistance.