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Reconstructing Evolving Tree Structures in Time Lapse Sequences by Enforcing Time-Consistency
2018
IEEE Transactions on Pattern Analysis and Machine Intelligence
We propose a novel approach to reconstructing curvilinear tree structures evolving over time, such as road networks in 2D aerial images or neural structures in 3D microscopy stacks acquired in vivo. To enforce temporal consistency, we simultaneously process all images in a sequence, as opposed to reconstructing structures of interest in each image independently. We formulate the problem as a Quadratic Mixed Integer Program and demonstrate the additional robustness that comes from using all
doi:10.1109/tpami.2017.2680444
pmid:28333621
fatcat:ui44zruzuvdf3ihew65f7nlnym