Toward an Automatic System for Computer-Aided Assessment in Facial Palsy

Quantitative assessment of facial function is challenging, and subjective grading scales such as House-Brackmann, Sunnybrook, and eFACE have well-recognized limitations. Machine learning (ML) approaches to facial landmark localization carry great clinical potential as they enable high-throughput aut...

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Veröffentlicht in:	Facial plastic surgery & aesthetic medicine Jg. 22; H. 1; S. 42
Hauptverfasser:	Guarin, Diego L, Yunusova, Yana, Taati, Babak, Dusseldorp, Joseph R, Mohan, Suresh, Tavares, Joana, van Veen, Martinus M, Fortier, Emily, Hadlock, Tessa A, Jowett, Nate
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States 01.02.2020
Schlagworte:	Adolescent Adult Aged Aged, 80 and over Anatomic Landmarks Child Diagnosis, Computer-Assisted Facial Expression Facial Paralysis - diagnosis Female Humans Machine Learning Male Middle Aged Photography
ISSN:	2689-3622, 2689-3622
Online-Zugang:	Weitere Angaben
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