We propose a coercive approach to simultaneously register and segment
multi-modal images which share similar spatial structure. Registration is done
at the region level to facilitate data fusion while avoiding the need for
interpolation. The algorithm performs alternating minimization of an objective
function informed by statistical models for pixel values in different
modalities. Hypothesis tests are developed to determine whether to refine
segmentations by splitting regions. We demonstrate that our approach has
significantly better performance than the state-of-the-art registration and
segmentation methods on microscopy images.Comment: This work has been accepted to International Conference on Image
Processing (ICIP) 201