A deep generative model of 3D single-cell organization

We introduce a framework for end-to-end integrative modeling of 3D single-cell multi-channel fluorescent image data of diverse subcellular structures. We employ stacked conditional β -variational autoencoders to first learn a latent representation of cell morphology, and then learn a latent repre…