Coercive Region-level Registration for Multi-modal Images

2015/02/26 by Yu-Hui Chen, Chen, Yu-Hui, Dennis Wei +7
Computer Science · Physics and Astronomy · #Computer Vision and Pattern Recognition (cs.CV) #Data Analysis #FOS: Computer and information sciences #FOS: Physical sciences #Statistics and Probability (physics.data-an) #cs.CV #physics.data-an

paper · pdf · doi:10.48550/arxiv.1502.07432

This work has been accepted to International Conference on Image Processing (ICIP) 2015

arxiv created 2015/11/18 · arxiv updated 2015/11/19

Abstract

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.

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