Clinical application of an automatic facial recognition system based on deep learning for diagnosis of Turner syndrome

Pan, Zhouxian; Shen, Zhen; Zhu, Huijuan; Bao, Yuhai; Liang, Siyu; Wang, Shirui; Li, Xiangying; Niu, Lulu; Dong, Xisong; Shang, Xiuqin; Shi, Chuang; Pan, Hui; Xiong, Gang

doi:10.1007/s12020-020-02539-3

Cited by 30 publications

(29 citation statements)

References 18 publications

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“…For example, genetic disorders such as Turner syndrome and Down syndrome all have remarkable facial changes. In recent years, studies have applied facial recognition algorithms in the diagnosis of these diseases (30,31). Thanks to the technological advance in 3D facial recognition, diagnosis based on 3D virtual models has the potential to yield better accuracy.…”

Section: Clinical Relevancementioning

confidence: 99%

Three-dimensional facial scanner in the hands of patients: validation of a novel application on iPad/iPhone for three-dimensional imaging

Chong¹,

Liu²,

Shi³

et al. 2021

Ann Transl Med

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Background: Three-dimensional (3D) photography plays an important role in surgical planning and postoperative evaluation. Commercial 3D facial scanners are expensive, and they require patients to come to the clinics for 3D photography. To solve this problem, we developed an iPad/iPhone application to enable patients to capture 3D images of themselves on their own. This study aimed to evaluate the validity and reproducibility of this novel imaging system. Methods: 3D images were taken on 20 volunteers using the novel imaging system. Twenty-one anthropometric parameters were measured using calipers (direct measurement) and 3D photographs (3D photogrammetry). The results were compared to assess the accuracy and bias of 3D photogrammetry. The reproducibility was evaluated by testing intra-and interobserver reliabilities. Furthermore, 3D virtual models obtained by the novel imaging system and Vectra H1 camera were compared by performing heat map analysis. Results: The 3D photogrammetric results showed excellent correlations with direct measurements. Most anthropometric parameters did not show statistically significant differences between the two methods. The 95% limits of agreement exceeded 2 mm in some parameters, especially those with large numbers, although their relative error measurements were very small. Intra-and interobserver reliabilities were high enough to ensure good reproducibility. The comparison of 3D models obtained by the novel imaging system and Vectra H1 camera showed that the mean distance and the mean RMS were 0.08 and 0.67 mm, respectively. Conclusions: The novel 3D facial scanning system is validated to enable patients to take 3D images on their own. The imaging quality of the subnasale region needs further improvement. Future clinical applications include surgical planning, postoperative evaluation, and early diagnosis of diseases that affect facial appearance.

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Section: Clinical Relevancementioning

confidence: 99%

Three-dimensional facial scanner in the hands of patients: validation of a novel application on iPad/iPhone for three-dimensional imaging

Chong¹,

Liu²,

Shi³

et al. 2021

Ann Transl Med

View full text Add to dashboard Cite

show abstract

“…In the human context, facial analysis platforms have long been in use for various applications, such as password systems on smartphones, identification at international border checkpoints, identification of criminals [5], diagnosis of Turner syndrome [6], detection of genetic disorder phenotypes [7], as a potential diagnostic tool for Parkinson disease [8], measuring tourist satisfaction through emotional expressions [9], and quantification of customer interest during shopping [10].…”

Section: Introductionmentioning

confidence: 99%

Happy Cow or Thinking Pig? WUR Wolf—Facial Coding Platform for Measuring Emotions in Farm Animals

Neethirajan

2021

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Emotions play an indicative and informative role in the investigation of farm animal behaviors. Systems that respond and can measure emotions provide a natural user interface in enabling the digitalization of animal welfare platforms. The faces of farm animals can be one of the richest channels for expressing emotions. WUR Wolf (Wageningen University & Research: Wolf Mascot), a real-time facial recognition platform that can automatically code the emotions of farm animals, is presented in this study. The developed Python-based algorithms detect and track the facial features of cows and pigs, analyze the appearance, ear postures, and eye white regions, and correlate these with the mental/emotional states of the farm animals. The system is trained on a dataset of facial features of images of farm animals collected in over six farms and has been optimized to operate with an average accuracy of 85%. From these, the emotional states of animals in real time are determined. The software detects 13 facial actions and an inferred nine emotional states, including whether the animal is aggressive, calm, or neutral. A real-time emotion recognition system based on YoloV3, a Faster YoloV4-based facial detection platform and an ensemble Convolutional Neural Networks (RCNN) is presented. Detecting facial features of farm animals simultaneously in real time enables many new interfaces for automated decision-making tools for livestock farmers. Emotion sensing offers a vast potential for improving animal welfare and animal–human interactions.

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“…In the human context, facial recognition platforms have long been in use for various applications, such as password systems on smartphones, identification at international border checkpoints, identification of criminals [4, diagnosis of Turner syndrome [5]; detection of genetic disorder phenotypes [6]; as a potential diagnostic tool for Parkinson disease [7]; measuring tourist satisfaction through emotional expressions [8]; and quantification of customer interest during shopping [9].…”

Section: Introductionmentioning

confidence: 99%

Happy Cow or Thinking Pig? WUR Wolf – Facial Coding Platform for Measuring Emotions in Farm Animals

Neethirajan

2021

Preprint

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Emotions play an indicative and informative role in the investigation of farm animal behaviors. Systems that respond and can measure emotions provide a natural user interface in enabling the digitalization of animal welfare platforms. The faces of farm animals can be one of the richest channels for expressing emotions. We present WUR Wolf (Wageningen University & Research: Wolf Mascot)a real-time facial expression recognition platform that can automatically code the emotions of farm animals. Using Python-based algorithms, we detect and track the facial features of cows and pigs, analyze the appearance, ear postures, and eye white regions, and correlate with the mental/emotional states of the farm animals. The system is trained on dataset of facial features of images of the farm animals collected in over 6 farms and has been optimized to operate with an average accuracy of 85%. From these, we infer the emotional states of animals in real time. The software detects 13 facial actions and 9 emotional states, including whether the animal is ag-gressive, calm, or neutral. A real-time emotion recognition system based on YoloV3, and Faster YoloV4-based facial detection platform and an ensemble Convolutional Neural Networks (RCNN) is presented. Detecting expressions of farm animals simultaneously in real time makes many new interfaces for automated decision-making tools possible for livestock farmers. Emotions sensing offers a vast amount of potential for improving animal welfare and animal-human interactions.

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Clinical application of an automatic facial recognition system based on deep learning for diagnosis of Turner syndrome

Cited by 30 publications

References 18 publications

Three-dimensional facial scanner in the hands of patients: validation of a novel application on iPad/iPhone for three-dimensional imaging

Three-dimensional facial scanner in the hands of patients: validation of a novel application on iPad/iPhone for three-dimensional imaging

Happy Cow or Thinking Pig? WUR Wolf—Facial Coding Platform for Measuring Emotions in Farm Animals

Happy Cow or Thinking Pig? WUR Wolf – Facial Coding Platform for Measuring Emotions in Farm Animals

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