Evaluating the Impact of BoNT-A Injections on Facial Expressions: A Deep Learning Analysis.

IF 3 2区 医学 Q1 SURGERY Aesthetic Surgery Journal Pub Date : 2024-12-12 DOI:10.1093/asj/sjae204
Gulay Aktar Ugurlu, Burak Numan Ugurlu, Meryem Yalcinkaya
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引用次数: 0

Abstract

Background: Botulinum toxin type A (BoNT-A) injections are widely administered for facial rejuvenation, but their effects on facial expressions remain unclear.

Objectives: In this study, we aimed to objectively measure the impact of BoNT-A injections on facial expressions with deep learning techniques.

Methods: One hundred eighty patients age 25 to 60 years who underwent BoNT-A application to the upper face were included. Patients were photographed with neutral, happy, surprised, and angry expressions before and 14 days after the procedure. A convolutional neural network (CNN)-based facial emotion recognition (FER) system analyzed 1440 photographs with a hybrid data set of clinical images and the Karolinska Directed Emotional Faces (KDEF) data set.

Results: The CNN model accurately predicted 90.15% of the test images. Significant decreases in the recognition of angry and surprised expressions were observed postinjection (P < .05), with no significant changes in happy or neutral expressions (P > .05). Angry expressions were often misclassified as neutral or happy (P < .05), and surprised expressions were more likely to be perceived as neutral (P < .05).

Conclusions: Deep learning can effectively assess the impact of BoNT-A injections on facial expressions, providing more standardized data than traditional surveys. BoNT-A may reduce the expression of anger and surprise, potentially leading to a more positive facial appearance and emotional state. Further studies are needed to understand the broader implications of these changes.

Level of evidence: 4 (therapeutic):

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评估注射 BoNT-A 对面部表情的影响:深度学习分析
背景:肉毒杆菌毒素 A 型(BoNT-AA型肉毒杆菌毒素(BoNT-A)注射被广泛用于面部年轻化,但其对面部表情的影响仍不明确:本研究旨在利用深度学习技术客观测量 BoNT-A 注射对面部表情的影响。对患者术前和术后 14 天的中性、快乐、惊讶和愤怒表情进行拍照。基于卷积神经网络(CNN)的面部情绪识别(FER)系统使用临床图像混合数据集和卡罗林斯卡定向情绪面孔(KDEF)数据集分析了1440张照片:结果:CNN 模型准确预测了 90.15% 的测试图像。注射后,愤怒和惊讶表情的识别率显著下降(p0.05)。愤怒的表情经常被错误地分类为中性或快乐的表情(p结论:深度学习可以有效评估注射 BoNT-A 对面部表情的影响,提供比传统调查更标准化的数据。BoNT-A 可能会减少愤怒和惊讶的表达,从而可能导致更积极的面部表情和情绪状态。要了解这些变化的广泛影响,还需要进一步的研究。
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来源期刊
CiteScore
6.20
自引率
20.70%
发文量
309
审稿时长
6-12 weeks
期刊介绍: Aesthetic Surgery Journal is a peer-reviewed international journal focusing on scientific developments and clinical techniques in aesthetic surgery. The official publication of The Aesthetic Society, ASJ is also the official English-language journal of many major international societies of plastic, aesthetic and reconstructive surgery representing South America, Central America, Europe, Asia, and the Middle East. It is also the official journal of the British Association of Aesthetic Plastic Surgeons, the Canadian Society for Aesthetic Plastic Surgery and The Rhinoplasty Society.
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