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Automatic Craniomaxillofacial Landmark Digitization via Segmentation-guided Partially-joint Regression Forest Model and Multi-scale Statistical Features

OBJECTIVE: The goal of this paper is to automatically digitize craniomaxillofacial (CMF) landmarks efficiently and accurately from cone-beam computed tomography (CBCT) images, by addressing the challenge caused by large morphological variations across patients and image artifacts of CBCT images. MET...

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Dades bibliogràfiques
Publicat a:IEEE Trans Biomed Eng
Autors principals: Zhang, Jun, Gao, Yaozong, Wang, Li, Tang, Zhen, Xia, James J., Shen, Dinggang
Format: Artigo
Idioma:Inglês
Publicat: 2015
Matèries:
Accés en línia:https://ncbi.nlm.nih.gov/pmc/articles/PMC4879598/
https://ncbi.nlm.nih.gov/pubmed/26625402
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1109/TBME.2015.2503421
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