Otology & neurotology : official publication of the American Otological Society, American Neurotology Society [and] European Academy of Otology and Neurotology · 2020
Automatic Facial Recognition System Assisted-facial Asymmetry Scale Using Facial Landmarks.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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Lee Se A, Kim Jin, Lee Jeon Mi, Hong Yu-Jin, Kim Ig-Jae, Lee Jong Dae
Аннотация
OBJECTIVES: This study aimed to demonstrate the application of our automated facial recognition system to measure facial nerve function and compare its effectiveness with other conventional systems and provide a preliminary evaluation of deep learning-facial grading systems.
STUDY DESIGN: Retrospective, observational.
SETTING: Tertiary referral center, hospital.
PATIENTS: Facial photos taken from 128 patients with facial paralysis and two persons with no history of facial palsy were analyzed.
INTERVENTION: Diagnostic.
MAIN OUTCOME MEASURES: Correlation with Sunnybrook (SB) and House-Brackmann (HB) grading scales.
RESULTS: Our results had good reliability and correlation with other grading systems (r = 0.905 and 0.783 for Sunnybrook and HB grading scales, respectively), while being less time-consuming than Sunnybrook grading scale.
CONCLUSIONS: Our objective method shows good correlation with both Sunnybrook and HB grading systems. Furthermore, this system could be developed into an application for use with a variety of electronic devices, including smartphones and tablets.
STUDY DESIGN: Retrospective, observational.
SETTING: Tertiary referral center, hospital.
PATIENTS: Facial photos taken from 128 patients with facial paralysis and two persons with no history of facial palsy were analyzed.
INTERVENTION: Diagnostic.
MAIN OUTCOME MEASURES: Correlation with Sunnybrook (SB) and House-Brackmann (HB) grading scales.
RESULTS: Our results had good reliability and correlation with other grading systems (r = 0.905 and 0.783 for Sunnybrook and HB grading scales, respectively), while being less time-consuming than Sunnybrook grading scale.
CONCLUSIONS: Our objective method shows good correlation with both Sunnybrook and HB grading systems. Furthermore, this system could be developed into an application for use with a variety of electronic devices, including smartphones and tablets.