Automated Mathematical Algorithm for Quantitative Measurement of Strabismus Based on Photographs of Nine Cardinal Gaze Positions Article Swipe
Yena Christina Kang
,
Hee Kyung Yang
,
Young Jae Kim
,
Jeong‐Min Hwang
,
Kwang Gi Kim
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1155/2022/9840494
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1155/2022/9840494
This study presents an automated algorithm that measures ocular deviation quantitatively using photographs of the nine cardinal points of gaze by means of deep learning (DL) and image processing techniques. Photographs were collected from patients with strabismus. The images were used as inputs for the DL segmentation models that segmented the sclerae and limbi. Subsequently, the images were registered for the mathematical algorithm. Two‐dimensional sclera and limbus were modeled, and the corneal light reflex points of the primary gaze images were determined. Limbus recognition was performed to measure the pixel‐wise distance between the corneal reflex point and limbus center. The segmentation models exhibited high performance, with 96.88% dice similarity coefficient (DSC) for the sclera segmentation and 95.71% DSC for the limbus segmentation. The mathematical algorithm was tested on two cranial nerve palsy patients to evaluate its ability to measure and compare ocular deviation in different directions. These results were consistent with the symptoms of such disorders. This algorithm successfully measured the distance of ocular deviation in patients with strabismus. With complementation in the dimension calculations, we expect that this algorithm can be used further in clinical settings to diagnose and measure strabismus at a low cost.
Related Topics
Concepts
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1155/2022/9840494
- https://downloads.hindawi.com/journals/bmri/2022/9840494.pdf
- OA Status
- hybrid
- Cited By
- 13
- References
- 27
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4221031790
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4221031790Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1155/2022/9840494Digital Object Identifier
- Title
-
Automated Mathematical Algorithm for Quantitative Measurement of Strabismus Based on Photographs of Nine Cardinal Gaze PositionsWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-01-01Full publication date if available
- Authors
-
Yena Christina Kang, Hee Kyung Yang, Young Jae Kim, Jeong‐Min Hwang, Kwang Gi KimList of authors in order
- Landing page
-
https://doi.org/10.1155/2022/9840494Publisher landing page
- PDF URL
-
https://downloads.hindawi.com/journals/bmri/2022/9840494.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
hybridOpen access status per OpenAlex
- OA URL
-
https://downloads.hindawi.com/journals/bmri/2022/9840494.pdfDirect OA link when available
- Concepts
-
Sclera, Segmentation, Artificial intelligence, Computer science, Strabismus, Pixel, Algorithm, Gaze, Computer vision, Image segmentation, Mathematics, Medicine, Anatomy, OphthalmologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
13Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 4, 2024: 7, 2023: 1, 2022: 1Per-year citation counts (last 5 years)
- References (count)
-
27Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W4221031790 |
|---|---|
| doi | https://doi.org/10.1155/2022/9840494 |
| ids.doi | https://doi.org/10.1155/2022/9840494 |
| ids.pmid | https://pubmed.ncbi.nlm.nih.gov/35372579 |
| ids.openalex | https://openalex.org/W4221031790 |
| fwci | 2.69456169 |
| mesh[0].qualifier_ui | |
| mesh[0].descriptor_ui | D000465 |
| mesh[0].is_major_topic | True |
| mesh[0].qualifier_name | |
| mesh[0].descriptor_name | Algorithms |
| mesh[1].qualifier_ui | |
| mesh[1].descriptor_ui | D005123 |
| mesh[1].is_major_topic | False |
| mesh[1].qualifier_name | |
| mesh[1].descriptor_name | Eye |
| mesh[2].qualifier_ui | |
| mesh[2].descriptor_ui | D006801 |
| mesh[2].is_major_topic | False |
| mesh[2].qualifier_name | |
| mesh[2].descriptor_name | Humans |
| mesh[3].qualifier_ui | |
| mesh[3].descriptor_ui | D007091 |
| mesh[3].is_major_topic | False |
| mesh[3].qualifier_name | |
| mesh[3].descriptor_name | Image Processing, Computer-Assisted |
| mesh[4].qualifier_ui | Q000000981 |
| mesh[4].descriptor_ui | D013285 |
| mesh[4].is_major_topic | True |
| mesh[4].qualifier_name | diagnostic imaging |
| mesh[4].descriptor_name | Strabismus |
| mesh[5].qualifier_ui | |
| mesh[5].descriptor_ui | D000465 |
| mesh[5].is_major_topic | True |
| mesh[5].qualifier_name | |
| mesh[5].descriptor_name | Algorithms |
| mesh[6].qualifier_ui | |
| mesh[6].descriptor_ui | D005123 |
| mesh[6].is_major_topic | False |
| mesh[6].qualifier_name | |
| mesh[6].descriptor_name | Eye |
| mesh[7].qualifier_ui | |
| mesh[7].descriptor_ui | D006801 |
| mesh[7].is_major_topic | False |
| mesh[7].qualifier_name | |
| mesh[7].descriptor_name | Humans |
| mesh[8].qualifier_ui | |
| mesh[8].descriptor_ui | D007091 |
| mesh[8].is_major_topic | False |
| mesh[8].qualifier_name | |
| mesh[8].descriptor_name | Image Processing, Computer-Assisted |
| mesh[9].qualifier_ui | Q000000981 |
| mesh[9].descriptor_ui | D013285 |
| mesh[9].is_major_topic | True |
| mesh[9].qualifier_name | diagnostic imaging |
| mesh[9].descriptor_name | Strabismus |
| type | article |
| title | Automated Mathematical Algorithm for Quantitative Measurement of Strabismus Based on Photographs of Nine Cardinal Gaze Positions |
| awards[0].id | https://openalex.org/G6960573066 |
| awards[0].funder_id | https://openalex.org/F4320327848 |
| awards[0].display_name | |
| awards[0].funder_award_id | IITP-2021-2017-0-01630 |
| awards[0].funder_display_name | Gyeonggi-do Regional Research Center |
| biblio.issue | 1 |
| biblio.volume | 2022 |
| biblio.last_page | 9840494 |
| biblio.first_page | 9840494 |
| topics[0].id | https://openalex.org/T11538 |
| topics[0].field.id | https://openalex.org/fields/27 |
| topics[0].field.display_name | Medicine |
| topics[0].score | 0.9994000196456909 |
| topics[0].domain.id | https://openalex.org/domains/4 |
| topics[0].domain.display_name | Health Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/2734 |
| topics[0].subfield.display_name | Pathology and Forensic Medicine |
| topics[0].display_name | Ophthalmology and Eye Disorders |
| topics[1].id | https://openalex.org/T11194 |
| topics[1].field.id | https://openalex.org/fields/27 |
| topics[1].field.display_name | Medicine |
| topics[1].score | 0.994700014591217 |
| topics[1].domain.id | https://openalex.org/domains/4 |
| topics[1].domain.display_name | Health Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/2731 |
| topics[1].subfield.display_name | Ophthalmology |
| topics[1].display_name | Ocular Diseases and Behçet’s Syndrome |
| topics[2].id | https://openalex.org/T11929 |
| topics[2].field.id | https://openalex.org/fields/27 |
| topics[2].field.display_name | Medicine |
| topics[2].score | 0.9945999979972839 |
| topics[2].domain.id | https://openalex.org/domains/4 |
| topics[2].domain.display_name | Health Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/2728 |
| topics[2].subfield.display_name | Neurology |
| topics[2].display_name | Cerebral Venous Sinus Thrombosis |
| funders[0].id | https://openalex.org/F4320327848 |
| funders[0].ror | |
| funders[0].display_name | Gyeonggi-do Regional Research Center |
| is_xpac | False |
| apc_list.value | 2400 |
| apc_list.currency | USD |
| apc_list.value_usd | 2400 |
| apc_paid.value | 2400 |
| apc_paid.currency | USD |
| apc_paid.value_usd | 2400 |
| concepts[0].id | https://openalex.org/C2777100477 |
| concepts[0].level | 2 |
| concepts[0].score | 0.8316234350204468 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q193107 |
| concepts[0].display_name | Sclera |
| concepts[1].id | https://openalex.org/C89600930 |
| concepts[1].level | 2 |
| concepts[1].score | 0.6875580549240112 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q1423946 |
| concepts[1].display_name | Segmentation |
| concepts[2].id | https://openalex.org/C154945302 |
| concepts[2].level | 1 |
| concepts[2].score | 0.6187639832496643 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[2].display_name | Artificial intelligence |
| concepts[3].id | https://openalex.org/C41008148 |
| concepts[3].level | 0 |
| concepts[3].score | 0.5881814956665039 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[3].display_name | Computer science |
| concepts[4].id | https://openalex.org/C2776864138 |
| concepts[4].level | 2 |
| concepts[4].score | 0.4959898889064789 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q7620839 |
| concepts[4].display_name | Strabismus |
| concepts[5].id | https://openalex.org/C160633673 |
| concepts[5].level | 2 |
| concepts[5].score | 0.48410141468048096 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q355198 |
| concepts[5].display_name | Pixel |
| concepts[6].id | https://openalex.org/C11413529 |
| concepts[6].level | 1 |
| concepts[6].score | 0.45398324728012085 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q8366 |
| concepts[6].display_name | Algorithm |
| concepts[7].id | https://openalex.org/C2779916870 |
| concepts[7].level | 2 |
| concepts[7].score | 0.4529912769794464 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q14467155 |
| concepts[7].display_name | Gaze |
| concepts[8].id | https://openalex.org/C31972630 |
| concepts[8].level | 1 |
| concepts[8].score | 0.44444915652275085 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q844240 |
| concepts[8].display_name | Computer vision |
| concepts[9].id | https://openalex.org/C124504099 |
| concepts[9].level | 3 |
| concepts[9].score | 0.41782742738723755 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q56933 |
| concepts[9].display_name | Image segmentation |
| concepts[10].id | https://openalex.org/C33923547 |
| concepts[10].level | 0 |
| concepts[10].score | 0.36328747868537903 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q395 |
| concepts[10].display_name | Mathematics |
| concepts[11].id | https://openalex.org/C71924100 |
| concepts[11].level | 0 |
| concepts[11].score | 0.321161150932312 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q11190 |
| concepts[11].display_name | Medicine |
| concepts[12].id | https://openalex.org/C105702510 |
| concepts[12].level | 1 |
| concepts[12].score | 0.30480948090553284 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q514 |
| concepts[12].display_name | Anatomy |
| concepts[13].id | https://openalex.org/C118487528 |
| concepts[13].level | 1 |
| concepts[13].score | 0.23965385556221008 |
| concepts[13].wikidata | https://www.wikidata.org/wiki/Q161437 |
| concepts[13].display_name | Ophthalmology |
| keywords[0].id | https://openalex.org/keywords/sclera |
| keywords[0].score | 0.8316234350204468 |
| keywords[0].display_name | Sclera |
| keywords[1].id | https://openalex.org/keywords/segmentation |
| keywords[1].score | 0.6875580549240112 |
| keywords[1].display_name | Segmentation |
| keywords[2].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[2].score | 0.6187639832496643 |
| keywords[2].display_name | Artificial intelligence |
| keywords[3].id | https://openalex.org/keywords/computer-science |
| keywords[3].score | 0.5881814956665039 |
| keywords[3].display_name | Computer science |
| keywords[4].id | https://openalex.org/keywords/strabismus |
| keywords[4].score | 0.4959898889064789 |
| keywords[4].display_name | Strabismus |
| keywords[5].id | https://openalex.org/keywords/pixel |
| keywords[5].score | 0.48410141468048096 |
| keywords[5].display_name | Pixel |
| keywords[6].id | https://openalex.org/keywords/algorithm |
| keywords[6].score | 0.45398324728012085 |
| keywords[6].display_name | Algorithm |
| keywords[7].id | https://openalex.org/keywords/gaze |
| keywords[7].score | 0.4529912769794464 |
| keywords[7].display_name | Gaze |
| keywords[8].id | https://openalex.org/keywords/computer-vision |
| keywords[8].score | 0.44444915652275085 |
| keywords[8].display_name | Computer vision |
| keywords[9].id | https://openalex.org/keywords/image-segmentation |
| keywords[9].score | 0.41782742738723755 |
| keywords[9].display_name | Image segmentation |
| keywords[10].id | https://openalex.org/keywords/mathematics |
| keywords[10].score | 0.36328747868537903 |
| keywords[10].display_name | Mathematics |
| keywords[11].id | https://openalex.org/keywords/medicine |
| keywords[11].score | 0.321161150932312 |
| keywords[11].display_name | Medicine |
| keywords[12].id | https://openalex.org/keywords/anatomy |
| keywords[12].score | 0.30480948090553284 |
| keywords[12].display_name | Anatomy |
| keywords[13].id | https://openalex.org/keywords/ophthalmology |
| keywords[13].score | 0.23965385556221008 |
| keywords[13].display_name | Ophthalmology |
| language | en |
| locations[0].id | doi:10.1155/2022/9840494 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S1010394304 |
| locations[0].source.issn | 2314-6133, 2314-6141 |
| locations[0].source.type | journal |
| locations[0].source.is_oa | False |
| locations[0].source.issn_l | 2314-6133 |
| locations[0].source.is_core | True |
| locations[0].source.is_in_doaj | False |
| locations[0].source.display_name | BioMed Research International |
| locations[0].source.host_organization | https://openalex.org/P4310319869 |
| locations[0].source.host_organization_name | Hindawi Publishing Corporation |
| locations[0].source.host_organization_lineage | https://openalex.org/P4310319869 |
| locations[0].source.host_organization_lineage_names | Hindawi Publishing Corporation |
| locations[0].license | cc-by |
| locations[0].pdf_url | https://downloads.hindawi.com/journals/bmri/2022/9840494.pdf |
| locations[0].version | publishedVersion |
| locations[0].raw_type | journal-article |
| locations[0].license_id | https://openalex.org/licenses/cc-by |
| locations[0].is_accepted | True |
| locations[0].is_published | True |
| locations[0].raw_source_name | BioMed Research International |
| locations[0].landing_page_url | https://doi.org/10.1155/2022/9840494 |
| locations[1].id | pmid:35372579 |
| locations[1].is_oa | False |
| locations[1].source.id | https://openalex.org/S4306525036 |
| locations[1].source.issn | |
| locations[1].source.type | repository |
| locations[1].source.is_oa | False |
| locations[1].source.issn_l | |
| locations[1].source.is_core | False |
| locations[1].source.is_in_doaj | False |
| locations[1].source.display_name | PubMed |
| locations[1].source.host_organization | https://openalex.org/I1299303238 |
| locations[1].source.host_organization_name | National Institutes of Health |
| locations[1].source.host_organization_lineage | https://openalex.org/I1299303238 |
| locations[1].license | |
| locations[1].pdf_url | |
| locations[1].version | publishedVersion |
| locations[1].raw_type | |
| locations[1].license_id | |
| locations[1].is_accepted | True |
| locations[1].is_published | True |
| locations[1].raw_source_name | BioMed research international |
| locations[1].landing_page_url | https://pubmed.ncbi.nlm.nih.gov/35372579 |
| locations[2].id | pmh:oai:pubmedcentral.nih.gov:8970860 |
| locations[2].is_oa | True |
| locations[2].source.id | https://openalex.org/S2764455111 |
| locations[2].source.issn | |
| locations[2].source.type | repository |
| locations[2].source.is_oa | False |
| locations[2].source.issn_l | |
| locations[2].source.is_core | False |
| locations[2].source.is_in_doaj | False |
| locations[2].source.display_name | PubMed Central |
| locations[2].source.host_organization | https://openalex.org/I1299303238 |
| locations[2].source.host_organization_name | National Institutes of Health |
| locations[2].source.host_organization_lineage | https://openalex.org/I1299303238 |
| locations[2].license | other-oa |
| locations[2].pdf_url | |
| locations[2].version | submittedVersion |
| locations[2].raw_type | Text |
| locations[2].license_id | https://openalex.org/licenses/other-oa |
| locations[2].is_accepted | False |
| locations[2].is_published | False |
| locations[2].raw_source_name | Biomed Res Int |
| locations[2].landing_page_url | https://www.ncbi.nlm.nih.gov/pmc/articles/8970860 |
| indexed_in | crossref, pubmed |
| authorships[0].author.id | https://openalex.org/A5046626561 |
| authorships[0].author.orcid | https://orcid.org/0000-0001-7712-1992 |
| authorships[0].author.display_name | Yena Christina Kang |
| authorships[0].countries | KR |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I12832649 |
| authorships[0].affiliations[0].raw_affiliation_string | Department of Biomedical Engineering, Gil Medical Center, Gachon University College of Medicine, Incheon 21565, Republic of Korea |
| authorships[0].institutions[0].id | https://openalex.org/I12832649 |
| authorships[0].institutions[0].ror | https://ror.org/03ryywt80 |
| authorships[0].institutions[0].type | education |
| authorships[0].institutions[0].lineage | https://openalex.org/I12832649 |
| authorships[0].institutions[0].country_code | KR |
| authorships[0].institutions[0].display_name | Gachon University |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Yena Christina Kang |
| authorships[0].is_corresponding | False |
| authorships[0].raw_affiliation_strings | Department of Biomedical Engineering, Gil Medical Center, Gachon University College of Medicine, Incheon 21565, Republic of Korea |
| authorships[1].author.id | https://openalex.org/A5056942694 |
| authorships[1].author.orcid | https://orcid.org/0000-0002-1140-6036 |
| authorships[1].author.display_name | Hee Kyung Yang |
| authorships[1].countries | KR |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I2803058125 |
| authorships[1].affiliations[0].raw_affiliation_string | Department of Ophthalmology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seoul 03080, Republic of Korea |
| authorships[1].institutions[0].id | https://openalex.org/I2803058125 |
| authorships[1].institutions[0].ror | https://ror.org/00cb3km46 |
| authorships[1].institutions[0].type | healthcare |
| authorships[1].institutions[0].lineage | https://openalex.org/I2802835388, https://openalex.org/I2803058125 |
| authorships[1].institutions[0].country_code | KR |
| authorships[1].institutions[0].display_name | Seoul National University Bundang Hospital |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Hee Kyung Yang |
| authorships[1].is_corresponding | False |
| authorships[1].raw_affiliation_strings | Department of Ophthalmology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seoul 03080, Republic of Korea |
| authorships[2].author.id | https://openalex.org/A5100650652 |
| authorships[2].author.orcid | https://orcid.org/0000-0003-0443-0051 |
| authorships[2].author.display_name | Young Jae Kim |
| authorships[2].countries | KR |
| authorships[2].affiliations[0].institution_ids | https://openalex.org/I12832649 |
| authorships[2].affiliations[0].raw_affiliation_string | Department of Biomedical Engineering, Gil Medical Center, Gachon University College of Medicine, Incheon 21565, Republic of Korea |
| authorships[2].institutions[0].id | https://openalex.org/I12832649 |
| authorships[2].institutions[0].ror | https://ror.org/03ryywt80 |
| authorships[2].institutions[0].type | education |
| authorships[2].institutions[0].lineage | https://openalex.org/I12832649 |
| authorships[2].institutions[0].country_code | KR |
| authorships[2].institutions[0].display_name | Gachon University |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Young Jae Kim |
| authorships[2].is_corresponding | False |
| authorships[2].raw_affiliation_strings | Department of Biomedical Engineering, Gil Medical Center, Gachon University College of Medicine, Incheon 21565, Republic of Korea |
| authorships[3].author.id | https://openalex.org/A5044926683 |
| authorships[3].author.orcid | https://orcid.org/0000-0003-0837-2864 |
| authorships[3].author.display_name | Jeong‐Min Hwang |
| authorships[3].countries | KR |
| authorships[3].affiliations[0].institution_ids | https://openalex.org/I2803058125 |
| authorships[3].affiliations[0].raw_affiliation_string | Department of Ophthalmology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seoul 03080, Republic of Korea |
| authorships[3].institutions[0].id | https://openalex.org/I2803058125 |
| authorships[3].institutions[0].ror | https://ror.org/00cb3km46 |
| authorships[3].institutions[0].type | healthcare |
| authorships[3].institutions[0].lineage | https://openalex.org/I2802835388, https://openalex.org/I2803058125 |
| authorships[3].institutions[0].country_code | KR |
| authorships[3].institutions[0].display_name | Seoul National University Bundang Hospital |
| authorships[3].author_position | middle |
| authorships[3].raw_author_name | Jeong-Min Hwang |
| authorships[3].is_corresponding | True |
| authorships[3].raw_affiliation_strings | Department of Ophthalmology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seoul 03080, Republic of Korea |
| authorships[4].author.id | https://openalex.org/A5073765158 |
| authorships[4].author.orcid | https://orcid.org/0000-0001-9714-6038 |
| authorships[4].author.display_name | Kwang Gi Kim |
| authorships[4].countries | KR |
| authorships[4].affiliations[0].institution_ids | https://openalex.org/I12832649 |
| authorships[4].affiliations[0].raw_affiliation_string | Department of Biomedical Engineering, Gil Medical Center, Gachon University College of Medicine, Incheon 21565, Republic of Korea |
| authorships[4].institutions[0].id | https://openalex.org/I12832649 |
| authorships[4].institutions[0].ror | https://ror.org/03ryywt80 |
| authorships[4].institutions[0].type | education |
| authorships[4].institutions[0].lineage | https://openalex.org/I12832649 |
| authorships[4].institutions[0].country_code | KR |
| authorships[4].institutions[0].display_name | Gachon University |
| authorships[4].author_position | last |
| authorships[4].raw_author_name | Kwang Gi Kim |
| authorships[4].is_corresponding | True |
| authorships[4].raw_affiliation_strings | Department of Biomedical Engineering, Gil Medical Center, Gachon University College of Medicine, Incheon 21565, Republic of Korea |
| has_content.pdf | True |
| has_content.grobid_xml | True |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://downloads.hindawi.com/journals/bmri/2022/9840494.pdf |
| open_access.oa_status | hybrid |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Automated Mathematical Algorithm for Quantitative Measurement of Strabismus Based on Photographs of Nine Cardinal Gaze Positions |
| has_fulltext | True |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T11538 |
| primary_topic.field.id | https://openalex.org/fields/27 |
| primary_topic.field.display_name | Medicine |
| primary_topic.score | 0.9994000196456909 |
| primary_topic.domain.id | https://openalex.org/domains/4 |
| primary_topic.domain.display_name | Health Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/2734 |
| primary_topic.subfield.display_name | Pathology and Forensic Medicine |
| primary_topic.display_name | Ophthalmology and Eye Disorders |
| related_works | https://openalex.org/W4231764886, https://openalex.org/W144671092, https://openalex.org/W2353746516, https://openalex.org/W2081283125, https://openalex.org/W3035533296, https://openalex.org/W198092683, https://openalex.org/W2394638302, https://openalex.org/W2351695492, https://openalex.org/W4290368984, https://openalex.org/W2389049781 |
| cited_by_count | 13 |
| counts_by_year[0].year | 2025 |
| counts_by_year[0].cited_by_count | 4 |
| counts_by_year[1].year | 2024 |
| counts_by_year[1].cited_by_count | 7 |
| counts_by_year[2].year | 2023 |
| counts_by_year[2].cited_by_count | 1 |
| counts_by_year[3].year | 2022 |
| counts_by_year[3].cited_by_count | 1 |
| locations_count | 3 |
| best_oa_location.id | doi:10.1155/2022/9840494 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S1010394304 |
| best_oa_location.source.issn | 2314-6133, 2314-6141 |
| best_oa_location.source.type | journal |
| best_oa_location.source.is_oa | False |
| best_oa_location.source.issn_l | 2314-6133 |
| best_oa_location.source.is_core | True |
| best_oa_location.source.is_in_doaj | False |
| best_oa_location.source.display_name | BioMed Research International |
| best_oa_location.source.host_organization | https://openalex.org/P4310319869 |
| best_oa_location.source.host_organization_name | Hindawi Publishing Corporation |
| best_oa_location.source.host_organization_lineage | https://openalex.org/P4310319869 |
| best_oa_location.source.host_organization_lineage_names | Hindawi Publishing Corporation |
| best_oa_location.license | cc-by |
| best_oa_location.pdf_url | https://downloads.hindawi.com/journals/bmri/2022/9840494.pdf |
| best_oa_location.version | publishedVersion |
| best_oa_location.raw_type | journal-article |
| best_oa_location.license_id | https://openalex.org/licenses/cc-by |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | True |
| best_oa_location.raw_source_name | BioMed Research International |
| best_oa_location.landing_page_url | https://doi.org/10.1155/2022/9840494 |
| primary_location.id | doi:10.1155/2022/9840494 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S1010394304 |
| primary_location.source.issn | 2314-6133, 2314-6141 |
| primary_location.source.type | journal |
| primary_location.source.is_oa | False |
| primary_location.source.issn_l | 2314-6133 |
| primary_location.source.is_core | True |
| primary_location.source.is_in_doaj | False |
| primary_location.source.display_name | BioMed Research International |
| primary_location.source.host_organization | https://openalex.org/P4310319869 |
| primary_location.source.host_organization_name | Hindawi Publishing Corporation |
| primary_location.source.host_organization_lineage | https://openalex.org/P4310319869 |
| primary_location.source.host_organization_lineage_names | Hindawi Publishing Corporation |
| primary_location.license | cc-by |
| primary_location.pdf_url | https://downloads.hindawi.com/journals/bmri/2022/9840494.pdf |
| primary_location.version | publishedVersion |
| primary_location.raw_type | journal-article |
| primary_location.license_id | https://openalex.org/licenses/cc-by |
| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | BioMed Research International |
| primary_location.landing_page_url | https://doi.org/10.1155/2022/9840494 |
| publication_date | 2022-01-01 |
| publication_year | 2022 |
| referenced_works | https://openalex.org/W1995426767, https://openalex.org/W2940939835, https://openalex.org/W2791449722, https://openalex.org/W2560758186, https://openalex.org/W2143654775, https://openalex.org/W2026677185, https://openalex.org/W2106306052, https://openalex.org/W1513732959, https://openalex.org/W2053056469, https://openalex.org/W2801353795, https://openalex.org/W2979721925, https://openalex.org/W2734954405, https://openalex.org/W2051267025, https://openalex.org/W1989369677, https://openalex.org/W3033039186, https://openalex.org/W3006135495, https://openalex.org/W1901129140, https://openalex.org/W1978642024, https://openalex.org/W2036714469, https://openalex.org/W2592674640, https://openalex.org/W3172469186, https://openalex.org/W2005982794, https://openalex.org/W2756491339, https://openalex.org/W3122908429, https://openalex.org/W2034038069, https://openalex.org/W2919956804, https://openalex.org/W1987681324 |
| referenced_works_count | 27 |
| abstract_inverted_index.a | 193 |
| abstract_inverted_index.DL | 45 |
| abstract_inverted_index.an | 3 |
| abstract_inverted_index.as | 41 |
| abstract_inverted_index.at | 192 |
| abstract_inverted_index.be | 181 |
| abstract_inverted_index.by | 20 |
| abstract_inverted_index.in | 143, 165, 171, 184 |
| abstract_inverted_index.of | 13, 18, 22, 75, 153, 162 |
| abstract_inverted_index.on | 127 |
| abstract_inverted_index.to | 86, 133, 137, 187 |
| abstract_inverted_index.we | 175 |
| abstract_inverted_index.DSC | 117 |
| abstract_inverted_index.The | 37, 99, 122 |
| abstract_inverted_index.and | 26, 52, 65, 69, 96, 115, 139, 189 |
| abstract_inverted_index.can | 180 |
| abstract_inverted_index.for | 43, 59, 111, 118 |
| abstract_inverted_index.its | 135 |
| abstract_inverted_index.low | 194 |
| abstract_inverted_index.the | 14, 44, 50, 55, 60, 70, 76, 88, 92, 112, 119, 151, 160, 172 |
| abstract_inverted_index.two | 128 |
| abstract_inverted_index.was | 84, 125 |
| abstract_inverted_index.(DL) | 25 |
| abstract_inverted_index.This | 0, 156 |
| abstract_inverted_index.With | 169 |
| abstract_inverted_index.deep | 23 |
| abstract_inverted_index.dice | 107 |
| abstract_inverted_index.from | 33 |
| abstract_inverted_index.gaze | 19, 78 |
| abstract_inverted_index.high | 103 |
| abstract_inverted_index.nine | 15 |
| abstract_inverted_index.such | 154 |
| abstract_inverted_index.that | 6, 48, 177 |
| abstract_inverted_index.this | 178 |
| abstract_inverted_index.used | 40, 182 |
| abstract_inverted_index.were | 31, 39, 57, 67, 80, 148 |
| abstract_inverted_index.with | 35, 105, 150, 167 |
| abstract_inverted_index.(DSC) | 110 |
| abstract_inverted_index.These | 146 |
| abstract_inverted_index.cost. | 195 |
| abstract_inverted_index.image | 27 |
| abstract_inverted_index.light | 72 |
| abstract_inverted_index.means | 21 |
| abstract_inverted_index.nerve | 130 |
| abstract_inverted_index.palsy | 131 |
| abstract_inverted_index.point | 95 |
| abstract_inverted_index.study | 1 |
| abstract_inverted_index.using | 11 |
| abstract_inverted_index.95.71% | 116 |
| abstract_inverted_index.96.88% | 106 |
| abstract_inverted_index.Limbus | 82 |
| abstract_inverted_index.expect | 176 |
| abstract_inverted_index.images | 38, 56, 79 |
| abstract_inverted_index.inputs | 42 |
| abstract_inverted_index.limbi. | 53 |
| abstract_inverted_index.limbus | 66, 97, 120 |
| abstract_inverted_index.models | 47, 101 |
| abstract_inverted_index.ocular | 8, 141, 163 |
| abstract_inverted_index.points | 17, 74 |
| abstract_inverted_index.reflex | 73, 94 |
| abstract_inverted_index.sclera | 64, 113 |
| abstract_inverted_index.tested | 126 |
| abstract_inverted_index.ability | 136 |
| abstract_inverted_index.between | 91 |
| abstract_inverted_index.center. | 98 |
| abstract_inverted_index.compare | 140 |
| abstract_inverted_index.corneal | 71, 93 |
| abstract_inverted_index.cranial | 129 |
| abstract_inverted_index.further | 183 |
| abstract_inverted_index.measure | 87, 138, 190 |
| abstract_inverted_index.primary | 77 |
| abstract_inverted_index.results | 147 |
| abstract_inverted_index.sclerae | 51 |
| abstract_inverted_index.cardinal | 16 |
| abstract_inverted_index.clinical | 185 |
| abstract_inverted_index.diagnose | 188 |
| abstract_inverted_index.distance | 90, 161 |
| abstract_inverted_index.evaluate | 134 |
| abstract_inverted_index.learning | 24 |
| abstract_inverted_index.measured | 159 |
| abstract_inverted_index.measures | 7 |
| abstract_inverted_index.modeled, | 68 |
| abstract_inverted_index.patients | 34, 132, 166 |
| abstract_inverted_index.presents | 2 |
| abstract_inverted_index.settings | 186 |
| abstract_inverted_index.symptoms | 152 |
| abstract_inverted_index.algorithm | 5, 124, 157, 179 |
| abstract_inverted_index.automated | 4 |
| abstract_inverted_index.collected | 32 |
| abstract_inverted_index.deviation | 9, 142, 164 |
| abstract_inverted_index.different | 144 |
| abstract_inverted_index.dimension | 173 |
| abstract_inverted_index.exhibited | 102 |
| abstract_inverted_index.performed | 85 |
| abstract_inverted_index.segmented | 49 |
| abstract_inverted_index.algorithm. | 62 |
| abstract_inverted_index.consistent | 149 |
| abstract_inverted_index.disorders. | 155 |
| abstract_inverted_index.processing | 28 |
| abstract_inverted_index.registered | 58 |
| abstract_inverted_index.similarity | 108 |
| abstract_inverted_index.strabismus | 191 |
| abstract_inverted_index.Photographs | 30 |
| abstract_inverted_index.coefficient | 109 |
| abstract_inverted_index.determined. | 81 |
| abstract_inverted_index.directions. | 145 |
| abstract_inverted_index.photographs | 12 |
| abstract_inverted_index.recognition | 83 |
| abstract_inverted_index.strabismus. | 36, 168 |
| abstract_inverted_index.techniques. | 29 |
| abstract_inverted_index.mathematical | 61, 123 |
| abstract_inverted_index.performance, | 104 |
| abstract_inverted_index.pixel‐wise | 89 |
| abstract_inverted_index.segmentation | 46, 100, 114 |
| abstract_inverted_index.successfully | 158 |
| abstract_inverted_index.Subsequently, | 54 |
| abstract_inverted_index.calculations, | 174 |
| abstract_inverted_index.segmentation. | 121 |
| abstract_inverted_index.quantitatively | 10 |
| abstract_inverted_index.complementation | 170 |
| abstract_inverted_index.Two‐dimensional | 63 |
| cited_by_percentile_year.max | 99 |
| cited_by_percentile_year.min | 89 |
| corresponding_author_ids | https://openalex.org/A5044926683, https://openalex.org/A5073765158 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 5 |
| corresponding_institution_ids | https://openalex.org/I12832649, https://openalex.org/I2803058125 |
| citation_normalized_percentile.value | 0.86445283 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |