Analysis of surgical outcome after upper eyelid surgery by computer vision algorithm using face and facial landmark detection
Purpose To evaluate the postoperative changes with a computer vision algorithm for anterior full-face photographs of patients who have undergone upper eyelid blepharoplasty surgery with, or without, a Müller’s muscle-conjunctival resection (MMCR). Methods All patients who underwent upper eyelid blep...
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| Vydáno v: | Graefe's archive for clinical and experimental ophthalmology Ročník 259; číslo 10; s. 3119 - 3125 |
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| Médium: | Journal Article |
| Jazyk: | angličtina |
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Berlin/Heidelberg
Springer Berlin Heidelberg
01.10.2021
Springer Nature B.V |
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| ISSN: | 0721-832X, 1435-702X, 1435-702X |
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| Abstract | Purpose
To evaluate the postoperative changes with a computer vision algorithm for anterior full-face photographs of patients who have undergone upper eyelid blepharoplasty surgery with, or without, a Müller’s muscle-conjunctival resection (MMCR).
Methods
All patients who underwent upper eyelid blepharoplasty surgery (Group I), or upper eyelid blepharoplasty with MMCR (Group II) were included. Both preoperative and 6-month postoperative anterior full-face photographs of 55 patients were analyzed. Computer vision and image processing technologies were used to measure the palpebral distance (PD), eye-opening area (EA), and average eyebrow height (AEBH) for both eyes. Preoperative and postoperative measurements were calculated and compared between the two groups.
Results
In Group II, change in postoperative Right PD, Left PD, Right EA, Left EA was significantly higher than in Group I (
p
= 0.004 for REPD;
p
= 0.001 for LEPD;
p
= 0.004 for REA;
p
= 0.002 for LEA,
p
< 0.05). In Group II, the postoperative change in Right AEBH, Left AEBH was significantly higher than in Group I (
p
= 0.001 for RABH and LABH,
p
< 0.05).
Conclusion
Eyelid surgery for esthetic purposes requires artistic judgment and objective evaluation. Because of the slight differences in photograph sizes and dynamic factors of the face due to head movements and facial expressions, it is hard to compare and make a truly objective evaluation of the eyelid operations. With a computer vision algorithm, using the face and facial landmark detection system, the photographs are normalized and calibrated. This system offers a simple, standardized, objective, and repeatable method of patient assessment. This can be the first step of Artificial Intelligence algorithm to evaluate the patients who had undergone eyelid operations. |
|---|---|
| AbstractList | Purpose
To evaluate the postoperative changes with a computer vision algorithm for anterior full-face photographs of patients who have undergone upper eyelid blepharoplasty surgery with, or without, a Müller’s muscle-conjunctival resection (MMCR).
Methods
All patients who underwent upper eyelid blepharoplasty surgery (Group I), or upper eyelid blepharoplasty with MMCR (Group II) were included. Both preoperative and 6-month postoperative anterior full-face photographs of 55 patients were analyzed. Computer vision and image processing technologies were used to measure the palpebral distance (PD), eye-opening area (EA), and average eyebrow height (AEBH) for both eyes. Preoperative and postoperative measurements were calculated and compared between the two groups.
Results
In Group II, change in postoperative Right PD, Left PD, Right EA, Left EA was significantly higher than in Group I (
p
= 0.004 for REPD;
p
= 0.001 for LEPD;
p
= 0.004 for REA;
p
= 0.002 for LEA,
p
< 0.05). In Group II, the postoperative change in Right AEBH, Left AEBH was significantly higher than in Group I (
p
= 0.001 for RABH and LABH,
p
< 0.05).
Conclusion
Eyelid surgery for esthetic purposes requires artistic judgment and objective evaluation. Because of the slight differences in photograph sizes and dynamic factors of the face due to head movements and facial expressions, it is hard to compare and make a truly objective evaluation of the eyelid operations. With a computer vision algorithm, using the face and facial landmark detection system, the photographs are normalized and calibrated. This system offers a simple, standardized, objective, and repeatable method of patient assessment. This can be the first step of Artificial Intelligence algorithm to evaluate the patients who had undergone eyelid operations. To evaluate the postoperative changes with a computer vision algorithm for anterior full-face photographs of patients who have undergone upper eyelid blepharoplasty surgery with, or without, a Müller's muscle-conjunctival resection (MMCR). All patients who underwent upper eyelid blepharoplasty surgery (Group I), or upper eyelid blepharoplasty with MMCR (Group II) were included. Both preoperative and 6-month postoperative anterior full-face photographs of 55 patients were analyzed. Computer vision and image processing technologies were used to measure the palpebral distance (PD), eye-opening area (EA), and average eyebrow height (AEBH) for both eyes. Preoperative and postoperative measurements were calculated and compared between the two groups. In Group II, change in postoperative Right PD, Left PD, Right EA, Left EA was significantly higher than in Group I (p = 0.004 for REPD; p = 0.001 for LEPD; p = 0.004 for REA; p = 0.002 for LEA, p < 0.05). In Group II, the postoperative change in Right AEBH, Left AEBH was significantly higher than in Group I (p = 0.001 for RABH and LABH, p < 0.05). Eyelid surgery for esthetic purposes requires artistic judgment and objective evaluation. Because of the slight differences in photograph sizes and dynamic factors of the face due to head movements and facial expressions, it is hard to compare and make a truly objective evaluation of the eyelid operations. With a computer vision algorithm, using the face and facial landmark detection system, the photographs are normalized and calibrated. This system offers a simple, standardized, objective, and repeatable method of patient assessment. This can be the first step of Artificial Intelligence algorithm to evaluate the patients who had undergone eyelid operations. To evaluate the postoperative changes with a computer vision algorithm for anterior full-face photographs of patients who have undergone upper eyelid blepharoplasty surgery with, or without, a Müller's muscle-conjunctival resection (MMCR).PURPOSETo evaluate the postoperative changes with a computer vision algorithm for anterior full-face photographs of patients who have undergone upper eyelid blepharoplasty surgery with, or without, a Müller's muscle-conjunctival resection (MMCR).All patients who underwent upper eyelid blepharoplasty surgery (Group I), or upper eyelid blepharoplasty with MMCR (Group II) were included. Both preoperative and 6-month postoperative anterior full-face photographs of 55 patients were analyzed. Computer vision and image processing technologies were used to measure the palpebral distance (PD), eye-opening area (EA), and average eyebrow height (AEBH) for both eyes. Preoperative and postoperative measurements were calculated and compared between the two groups.METHODSAll patients who underwent upper eyelid blepharoplasty surgery (Group I), or upper eyelid blepharoplasty with MMCR (Group II) were included. Both preoperative and 6-month postoperative anterior full-face photographs of 55 patients were analyzed. Computer vision and image processing technologies were used to measure the palpebral distance (PD), eye-opening area (EA), and average eyebrow height (AEBH) for both eyes. Preoperative and postoperative measurements were calculated and compared between the two groups.In Group II, change in postoperative Right PD, Left PD, Right EA, Left EA was significantly higher than in Group I (p = 0.004 for REPD; p = 0.001 for LEPD; p = 0.004 for REA; p = 0.002 for LEA, p < 0.05). In Group II, the postoperative change in Right AEBH, Left AEBH was significantly higher than in Group I (p = 0.001 for RABH and LABH, p < 0.05).RESULTSIn Group II, change in postoperative Right PD, Left PD, Right EA, Left EA was significantly higher than in Group I (p = 0.004 for REPD; p = 0.001 for LEPD; p = 0.004 for REA; p = 0.002 for LEA, p < 0.05). In Group II, the postoperative change in Right AEBH, Left AEBH was significantly higher than in Group I (p = 0.001 for RABH and LABH, p < 0.05).Eyelid surgery for esthetic purposes requires artistic judgment and objective evaluation. Because of the slight differences in photograph sizes and dynamic factors of the face due to head movements and facial expressions, it is hard to compare and make a truly objective evaluation of the eyelid operations. With a computer vision algorithm, using the face and facial landmark detection system, the photographs are normalized and calibrated. This system offers a simple, standardized, objective, and repeatable method of patient assessment. This can be the first step of Artificial Intelligence algorithm to evaluate the patients who had undergone eyelid operations.CONCLUSIONEyelid surgery for esthetic purposes requires artistic judgment and objective evaluation. Because of the slight differences in photograph sizes and dynamic factors of the face due to head movements and facial expressions, it is hard to compare and make a truly objective evaluation of the eyelid operations. With a computer vision algorithm, using the face and facial landmark detection system, the photographs are normalized and calibrated. This system offers a simple, standardized, objective, and repeatable method of patient assessment. This can be the first step of Artificial Intelligence algorithm to evaluate the patients who had undergone eyelid operations. PurposeTo evaluate the postoperative changes with a computer vision algorithm for anterior full-face photographs of patients who have undergone upper eyelid blepharoplasty surgery with, or without, a Müller’s muscle-conjunctival resection (MMCR).MethodsAll patients who underwent upper eyelid blepharoplasty surgery (Group I), or upper eyelid blepharoplasty with MMCR (Group II) were included. Both preoperative and 6-month postoperative anterior full-face photographs of 55 patients were analyzed. Computer vision and image processing technologies were used to measure the palpebral distance (PD), eye-opening area (EA), and average eyebrow height (AEBH) for both eyes. Preoperative and postoperative measurements were calculated and compared between the two groups.ResultsIn Group II, change in postoperative Right PD, Left PD, Right EA, Left EA was significantly higher than in Group I (p = 0.004 for REPD; p = 0.001 for LEPD; p = 0.004 for REA; p = 0.002 for LEA, p < 0.05). In Group II, the postoperative change in Right AEBH, Left AEBH was significantly higher than in Group I (p = 0.001 for RABH and LABH, p < 0.05).ConclusionEyelid surgery for esthetic purposes requires artistic judgment and objective evaluation. Because of the slight differences in photograph sizes and dynamic factors of the face due to head movements and facial expressions, it is hard to compare and make a truly objective evaluation of the eyelid operations. With a computer vision algorithm, using the face and facial landmark detection system, the photographs are normalized and calibrated. This system offers a simple, standardized, objective, and repeatable method of patient assessment. This can be the first step of Artificial Intelligence algorithm to evaluate the patients who had undergone eyelid operations. |
| Author | Şirolu, Can Bahçeci Şimşek, İlke |
| Author_xml | – sequence: 1 givenname: İlke orcidid: 0000-0002-8499-6823 surname: Bahçeci Şimşek fullname: Bahçeci Şimşek, İlke email: ilke.simsek@yeditepe.edu.tr organization: Department of Ophthalmology, Oculoplastic Division, Yeditepe University Medical School – sequence: 2 givenname: Can surname: Şirolu fullname: Şirolu, Can organization: Department of Ophthalmology, Yeditepe University Medical School |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/33963919$$D View this record in MEDLINE/PubMed |
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| ContentType | Journal Article |
| Copyright | The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021. |
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| Keywords | Computer vision algorithm Ptosis surgery Upper eyelid blepharoplasty Müller’s muscle-conjunctival resection Artificial intelligence Face and facial landmark detection |
| Language | English |
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To evaluate the postoperative changes with a computer vision algorithm for anterior full-face photographs of patients who have undergone upper eyelid... To evaluate the postoperative changes with a computer vision algorithm for anterior full-face photographs of patients who have undergone upper eyelid... PurposeTo evaluate the postoperative changes with a computer vision algorithm for anterior full-face photographs of patients who have undergone upper eyelid... |
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| SubjectTerms | Algorithms Artificial Intelligence Blepharoplasty Blepharoptosis - diagnosis Blepharoptosis - surgery Computer vision Computers Eyelid Eyelids - surgery Face Humans Image processing Medicine Medicine & Public Health Oculoplastics and Orbit Ophthalmology Patients Pattern recognition Prohibitins Retrospective Studies Surgery Treatment Outcome Vision |
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| Title | Analysis of surgical outcome after upper eyelid surgery by computer vision algorithm using face and facial landmark detection |
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