Web: http://arxiv.org/abs/1904.04354

Sept. 20, 2022, 1:13 a.m. | Neslisah Torosdagli, Syed Anwar, Payal Verma, Denise K Liberton, Janice S. Lee, Wade W. Han, Ulas Bagci

cs.CV updates on arXiv.org arxiv.org

Purpose: We perform anatomical landmarking for craniomaxillofacial (CMF)
bones without explicitly segmenting them. Towards this, we propose a new simple
yet efficient deep network architecture, called \textit{relational reasoning
network (RRN)}, to accurately learn the local and the global relations among
the landmarks in CMF bones; specifically, mandible, maxilla, and nasal bones.


Approach: The proposed RRN works in an end-to-end manner, utilizing learned
relations of the landmarks based on dense-block units. For a given few
landmarks as input, RRN treats the …

arxiv network reasoning

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