We propose a fast, automatic and versatile framework for the segmentation of multiple anatomical structures from 2D and 3D images. We extend the work of [1] on implicit template deformation to multiple targets. Our variational formulation optimizes the non-rigid transformation of a set of templates according to image-derived forces. It embeds nonoverlapping constraints ensuring a consistent segmentation result. We demonstrate the potential of our approach on the segmentation of abdominal organs (liver, kidneys, spleen and gallbladder) through an evaluation on 50 CT volumes. Our method reaches state-of-the-art accuracy, ranging from 2mm (liver and kidneys) to 8mm (gallbladder).