An automatic screening method for strabismus detection based on image processing.
<h4>Purpose</h4>This study aims to provide an automatic strabismus screening method for people who live in remote areas with poor medical accessibility.<h4>Materials and methods</h4>The proposed method first utilizes a pretrained convolutional neural network-based face-detect...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2021-01-01
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| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0255643 |
| _version_ | 1818362904678760448 |
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| author | Xilang Huang Sang Joon Lee Chang Zoo Kim Seon Han Choi |
| author_facet | Xilang Huang Sang Joon Lee Chang Zoo Kim Seon Han Choi |
| author_sort | Xilang Huang |
| collection | DOAJ |
| description | <h4>Purpose</h4>This study aims to provide an automatic strabismus screening method for people who live in remote areas with poor medical accessibility.<h4>Materials and methods</h4>The proposed method first utilizes a pretrained convolutional neural network-based face-detection model and a detector for 68 facial landmarks to extract the eye region for a frontal facial image. Second, Otsu's binarization and the HSV color model are applied to the image to eliminate the influence of eyelashes and canthi. Then, the method samples all of the pixel points on the limbus and applies the least square method to obtain the coordinate of the pupil center. Lastly, we calculated the distances from the pupil center to the medial and lateral canthus to measure the deviation of the positional similarity of two eyes for strabismus screening.<h4>Result</h4>We used a total of 60 frontal facial images (30 strabismus images, 30 normal images) to validate the proposed method. The average value of the iris positional similarity of normal images was smaller than one of the strabismus images via the method (p-value<0.001). The sample mean and sample standard deviation of the positional similarity of the normal and strabismus images were 1.073 ± 0.014 and 0.039, as well as 1.924 ± 0.169 and 0.472, respectively.<h4>Conclusion</h4>The experimental results of 60 images show that the proposed method is a promising automatic strabismus screening method for people living in remote areas with poor medical accessibility. |
| first_indexed | 2024-12-13T21:40:00Z |
| format | Article |
| id | doaj.art-a6d04aec83934dde88e962c991ae3b8f |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-12-13T21:40:00Z |
| publishDate | 2021-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-a6d04aec83934dde88e962c991ae3b8f2022-12-21T23:30:35ZengPublic Library of Science (PLoS)PLoS ONE1932-62032021-01-01168e025564310.1371/journal.pone.0255643An automatic screening method for strabismus detection based on image processing.Xilang HuangSang Joon LeeChang Zoo KimSeon Han Choi<h4>Purpose</h4>This study aims to provide an automatic strabismus screening method for people who live in remote areas with poor medical accessibility.<h4>Materials and methods</h4>The proposed method first utilizes a pretrained convolutional neural network-based face-detection model and a detector for 68 facial landmarks to extract the eye region for a frontal facial image. Second, Otsu's binarization and the HSV color model are applied to the image to eliminate the influence of eyelashes and canthi. Then, the method samples all of the pixel points on the limbus and applies the least square method to obtain the coordinate of the pupil center. Lastly, we calculated the distances from the pupil center to the medial and lateral canthus to measure the deviation of the positional similarity of two eyes for strabismus screening.<h4>Result</h4>We used a total of 60 frontal facial images (30 strabismus images, 30 normal images) to validate the proposed method. The average value of the iris positional similarity of normal images was smaller than one of the strabismus images via the method (p-value<0.001). The sample mean and sample standard deviation of the positional similarity of the normal and strabismus images were 1.073 ± 0.014 and 0.039, as well as 1.924 ± 0.169 and 0.472, respectively.<h4>Conclusion</h4>The experimental results of 60 images show that the proposed method is a promising automatic strabismus screening method for people living in remote areas with poor medical accessibility.https://doi.org/10.1371/journal.pone.0255643 |
| spellingShingle | Xilang Huang Sang Joon Lee Chang Zoo Kim Seon Han Choi An automatic screening method for strabismus detection based on image processing. PLoS ONE |
| title | An automatic screening method for strabismus detection based on image processing. |
| title_full | An automatic screening method for strabismus detection based on image processing. |
| title_fullStr | An automatic screening method for strabismus detection based on image processing. |
| title_full_unstemmed | An automatic screening method for strabismus detection based on image processing. |
| title_short | An automatic screening method for strabismus detection based on image processing. |
| title_sort | automatic screening method for strabismus detection based on image processing |
| url | https://doi.org/10.1371/journal.pone.0255643 |
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