Evaluating the agreement and reliability of a web-based facial analysis tool for rhinoplasty

Topsakal, Oğuzhan; Akbaş, Mustafa İlhan; Smith, Bria Synae; Perez, Michael Francis; Guden, Ege Can; Çelikoyar, M. Mazhar

doi:10.1007/s11548-021-02423-z

Cited by 9 publications

(10 citation statements)

References 28 publications

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“…The markings can also slightly change from one rater (the person who does the marking) to another, and the reliability of the raters should be tested. [46] To achieve more accurate manual markings, several raters could be utilized, and then the average of the markings could be computed to reach a consensus. To reduce the results, the utilization of statistics can be extended to incorporate more heuristics.…”

Section: Resultsmentioning

confidence: 99%

Detecting Facial Landmarks on 3D Models Based on Geometric Properties—A Review of Algorithms, Enhancements, Additions and Open-Source Implementations

et al. 2023

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Facial landmark detection, a crucial aspect of face recognition, is widely used in various fields, such as facial surgeries, biometrics, and surveillance systems. With the advancement of affordable and capable 3D scanning technologies, research on automatically detecting facial landmarks on 3D models is gaining momentum. Utilizing the geometric properties of 3D facial models, researchers have developed algorithms for various landmarks with varying levels of accuracy. In this study, we reviewed existing literature and developed algorithms for thirty-eight landmarks using geometric properties and statistical information about facial measurements. The algorithms for thirty landmarks are original contributions to the literature. We provide the implementation of all the algorithms as open-source Python code, along with the pseudocode for both our algorithms and those found in the literature. To the best of our knowledge, this study covers the largest number of facial landmark detection algorithms based on the geometric properties of 3D models. This is the first study that provides the implementation of the algorithms along with detailed pseudocode. The results of the algorithms are presented by calculating the mean, median, standard deviation, minimum, and maximum of the errors and depicting the histogram for each landmark over a hundred 3D facial scans. The results show that geometric properties and statistics can be utilized to achieve more robust solutions for facial landmark detection.

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Section: Resultsmentioning

confidence: 99%

Detecting Facial Landmarks on 3D Models Based on Geometric Properties—A Review of Algorithms, Enhancements, Additions and Open-Source Implementations

et al. 2023

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“…While these algorithms can be used to compute area and volume on any 3D models, we showed the results and analysis for measuring certain regions on 3D face models. We have developed open-source code implementations of these algorithms, which are accessible on GitHub [7], and have integrated them into a web-based Facial Analysis tool [9], [10]. Our goal is to contribute to the progress of facial analysis, an essential component of pre and post-surgery evaluations.…”

Section: Discussionmentioning

confidence: 99%

“…[8]. For example, we have implemented the area and volume algorithms to enhance the facial analyzer tool that focuses on pre-and post-surgery analysis and evaluations needed for rhinoplasty [9], [10]. As facial plastic surgeries are more digitized and computerized guidance will be provided before, during, and after surgery, the importance of determining the amount of area and volume will increase.…”

Section: Introductionmentioning

confidence: 99%

Algorithms to Measure Area and Volume on 3D Face Models for Facial Surgeries

et al. 2023

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The increased availability and affordability of 3D scanning technology due to recent advancements have made pre and post-operative analysis for facial surgeries more convenient and accurate through the use of 3D patient scans. However, to perform a more comprehensive analysis using area and volume measurements, it is necessary to develop new software tools that include the appropriate algorithms. Without the right algorithms, any software tool cannot perform its intended tasks effectively. In this study, we introduce two algorithms along with their open-source code to calculate the surface area and volume of a specific subsection of a 3D model. The first algorithm partitions the area/volume into smaller segmentations and applies raycasting to find the points on the face surface, and then finds an approximate measurement depending on the resolution selected. In contrast, the second algorithm utilizes the vertex information stored in the 3D model file to calculate the area and volume measurements for the designated region. The advantage of the second algorithm is that it examines every point in the model, resulting in the highest degree of precision possible. We have also used ChatGPT to generate the code for area/volume calculation and found that the logic of the ChatGPT-generated code is surprisingly similar to the second algorithm. We have presented the results of the measurements on certain regions of the face for both of the algorithms and compared the temporal performance of the algorithms.

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“…Traditionally, a facial analysis is performed directly on a patient's face using a ruler or miter. However, this method can cause discomfort to patients and limit the reproducibility of the results [1]. Computer-assisted 2D images (photographic capture) have been widely used for the analysis of the face, although this involves the inherent drawback of representing the 3D structure of the face in 2D [2].…”

Section: Introductionmentioning

confidence: 99%

“…This novel addition to facial analysis is intended to significantly improve surgical outcomes and enhance the overall success of facial surgical procedures [12,13]. We have developed open-source algorithms to measure area and volume on a 3D facial model [13] and then utilized these algorithms to enhance the free web-based software called Face Analyzer [14] to help surgeons perform a more in-depth analysis of a patient's face [1]. The Face Analyzer software, hosted at digitized-rhinoplasty.com, is now capable of measuring the area and volume of certain regions, such as the dorsal hump, nasal dorsum, root of the nose (Radix), and tip of the nose, and it is based on several previous works [10,12,13].…”

Section: Introductionmentioning

confidence: 99%

Reliability and Agreement of Free Web-Based 3D Software for Computing Facial Area and Volume Measurements

Topsakal,

Sawyer,

Akinci

et al. 2024

BioMedInformatics

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Background: Facial surgeries require meticulous planning and outcome assessments, where facial analysis plays a critical role. This study introduces a new approach by utilizing three-dimensional (3D) imaging techniques, which are known for their ability to measure facial areas and volumes accurately. The purpose of this study is to introduce and evaluate a free web-based software application designed to take area and volume measurements on 3D models of patient faces. Methods: This study employed the online facial analysis software to conduct ten measurements on 3D models of subjects, including five measurements of area and five measurements of volume. These measurements were then compared with those obtained from the established 3D modeling software called Blender (version 3.2) using the Bland–Altman plot. To ensure accuracy, the intra-rater and inter-rater reliabilities of the web-based software were evaluated using the Intraclass Correlation Coefficient (ICC) method. Additionally, statistical assumptions such as normality and homoscedasticity were rigorously verified before analysis. Results: This study found that the web-based facial analysis software showed high agreement with the 3D software Blender within 95% confidence limits. Moreover, the online application demonstrated excellent intra-rater and inter-rater reliability in most analyses, as indicated by the ICC test. Conclusion: The findings suggest that the free online 3D software is reliable for facial analysis, particularly in measuring areas and volumes. This indicates its potential utility in enhancing surgical planning and evaluation in facial surgeries. This study underscores the software’s capability to improve surgical outcomes by integrating precise area and volume measurements into facial surgery planning and assessment processes.

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Evaluating the agreement and reliability of a web-based facial analysis tool for rhinoplasty

Cited by 9 publications

References 28 publications

Detecting Facial Landmarks on 3D Models Based on Geometric Properties—A Review of Algorithms, Enhancements, Additions and Open-Source Implementations

Detecting Facial Landmarks on 3D Models Based on Geometric Properties—A Review of Algorithms, Enhancements, Additions and Open-Source Implementations

Algorithms to Measure Area and Volume on 3D Face Models for Facial Surgeries

Reliability and Agreement of Free Web-Based 3D Software for Computing Facial Area and Volume Measurements

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