Dataset Information

Deep learning based discrimination of soft tissue profiles requiring orthognathic surgery by facial photographs.

ABSTRACT: Facial photographs of the subjects are often used in the diagnosis process of orthognathic surgery. The aim of this study was to determine whether convolutional neural networks (CNNs) can judge soft tissue profiles requiring orthognathic surgery using facial photographs alone. 822 subjects with dentofacial dysmorphosis and / or malocclusion were included. Facial photographs of front and right side were taken from all patients. Subjects who did not need orthognathic surgery were classified as Group I (411 subjects). Group II (411 subjects) was set up for cases requiring surgery. CNNs of VGG19 was used for machine learning. 366 of the total 410 data were correctly classified, yielding 89.3% accuracy. The values of accuracy, precision, recall, and F1 scores were 0.893, 0.912, 0.867, and 0.889, respectively. As a result of this study, it was found that CNNs can judge soft tissue profiles requiring orthognathic surgery relatively accurately with the photographs alone.

SUBMITTER: Jeong SH

PROVIDER: S-EPMC7529761 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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Deep learning based discrimination of soft tissue profiles requiring orthognathic surgery by facial photographs.

Jeong Seung Hyun SH Yun Jong Pil JP Yeom Han-Gyeol HG Lim Hun Jun HJ Lee Jun J Kim Bong Chul BC

Scientific reports 20201001 1

Facial photographs of the subjects are often used in the diagnosis process of orthognathic surgery. The aim of this study was to determine whether convolutional neural networks (CNNs) can judge soft tissue profiles requiring orthognathic surgery using facial photographs alone. 822 subjects with dentofacial dysmorphosis and / or malocclusion were included. Facial photographs of front and right side were taken from all patients. Subjects who did not need orthognathic surgery were classified as Gro ...[more]

PMID: 33004872

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Project description:Typically, before and after surgical correction faces are assessed on still images by surgeons, orthodontists, the patients, and family members. We hypothesized that judgment of faces in motion and by naïve raters may closer reflect the impact on patients' real life, and the treatment impact on e.g. career chances. Therefore we assessed faces from dysgnathic patients (Class II, III and Laterognathia) on video clips. Class I faces served as anchor and controls. Each patient's face was assessed twice before and after treatment in changing sequence, by 155 naïve raters with similar age to the patients. The raters provided independent estimates on aesthetic trait pairs like ugly /beautiful, and personality trait pairs like dominant /flexible. Furthermore the perception of attractiveness, intelligence, health, the persons' erotic aura, faithfulness, and five additional items were rated. We estimated the significance of the perceived treatment related differences and the respective effect size by general linear models for repeated measures. The obtained results were comparable to our previous rating on still images. There was an overall trend, that faces in video clips are rated along common stereotypes to a lesser extent than photographs. We observed significant class differences and treatment related changes of most aesthetic traits (e.g. beauty, attractiveness), these were comparable to intelligence, erotic aura and to some extend healthy appearance. While some personality traits (e.g. faithfulness) did not differ between the classes and between baseline and after treatment, we found that the intervention significantly and effectively altered the perception of the personality trait self-confidence. The effect size was highest in Class III patients, smallest in Class II patients, and in between for patients with Laterognathia. All dysgnathic patients benefitted from orthognathic surgery. We conclude that motion can mitigate marked stereotypes but does not entirely offset the mostly negative perception of dysgnathic faces.

Dataset Information

Deep learning based discrimination of soft tissue profiles requiring orthognathic surgery by facial photographs.

Publications

Deep learning based discrimination of soft tissue profiles requiring orthognathic surgery by facial photographs.

Similar Datasets

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