HVAngleEst: A Dataset for End-to-end Automated Hallux Valgus Angle Measurement from X-Ray Images
Abstract Accurate measurement of hallux valgus angle (HVA) and intermetatarsal angle (IMA) is essential for diagnosing hallux valgus and determining appropriate treatment strategies. Traditional manual measurement methods, while standardized, are time-consuming, labor-intensive, and subject to evalu...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-05-01
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| Series: | Scientific Data |
| Online Access: | https://doi.org/10.1038/s41597-025-05261-9 |
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| author | Qiong Wang Dongdong Ji Junhu Wang Liang Liu Xinquan Yang Yan Zhang Jingqi Liang Peilong Liu Hongmou Zhao |
| author_facet | Qiong Wang Dongdong Ji Junhu Wang Liang Liu Xinquan Yang Yan Zhang Jingqi Liang Peilong Liu Hongmou Zhao |
| author_sort | Qiong Wang |
| collection | DOAJ |
| description | Abstract Accurate measurement of hallux valgus angle (HVA) and intermetatarsal angle (IMA) is essential for diagnosing hallux valgus and determining appropriate treatment strategies. Traditional manual measurement methods, while standardized, are time-consuming, labor-intensive, and subject to evaluator bias. Recent advancements in deep learning have been applied to hallux valgus angle estimation, but the development of effective algorithms requires large, well-annotated datasets. Existing X-ray datasets are typically limited to cropped foot regions images, and only one dataset containing very few samples is publicly available. To address these challenges, we introduce HVAngleEst, the first large-scale, open-access dataset specifically designed for hallux valgus angle estimation. HVAngleEst comprises 1,382 X-ray images from 1,150 patients and includes comprehensive annotations, such as foot localization, hallux valgus angles, and line segments for each phalanx. This dataset enables fully automated, end-to-end hallux valgus angle estimation, reducing manual labor and eliminating evaluator bias. |
| format | Article |
| id | doaj-art-19f17e42d20d42a199617aedaa7f5dfc |
| institution | Kabale University |
| issn | 2052-4463 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Data |
| spelling | doaj-art-19f17e42d20d42a199617aedaa7f5dfc2025-08-24T11:07:18ZengNature PortfolioScientific Data2052-44632025-05-011211710.1038/s41597-025-05261-9HVAngleEst: A Dataset for End-to-end Automated Hallux Valgus Angle Measurement from X-Ray ImagesQiong Wang0Dongdong Ji1Junhu Wang2Liang Liu3Xinquan Yang4Yan Zhang5Jingqi Liang6Peilong Liu7Hongmou Zhao8Foot and Ankle Surgery Department, Honghui Hospital, Xi’an Jiaotong UniversityFoot and Ankle Surgery Department, Honghui Hospital, Xi’an Jiaotong UniversityFoot and Ankle Surgery Department, Honghui Hospital, Xi’an Jiaotong UniversityFoot and Ankle Surgery Department, Honghui Hospital, Xi’an Jiaotong UniversityFoot and Ankle Surgery Department, Honghui Hospital, Xi’an Jiaotong UniversityFoot and Ankle Surgery Department, Honghui Hospital, Xi’an Jiaotong UniversityFoot and Ankle Surgery Department, Honghui Hospital, Xi’an Jiaotong UniversityFoot and Ankle Surgery Department, Honghui Hospital, Xi’an Jiaotong UniversityFoot and Ankle Surgery Department, Honghui Hospital, Xi’an Jiaotong UniversityAbstract Accurate measurement of hallux valgus angle (HVA) and intermetatarsal angle (IMA) is essential for diagnosing hallux valgus and determining appropriate treatment strategies. Traditional manual measurement methods, while standardized, are time-consuming, labor-intensive, and subject to evaluator bias. Recent advancements in deep learning have been applied to hallux valgus angle estimation, but the development of effective algorithms requires large, well-annotated datasets. Existing X-ray datasets are typically limited to cropped foot regions images, and only one dataset containing very few samples is publicly available. To address these challenges, we introduce HVAngleEst, the first large-scale, open-access dataset specifically designed for hallux valgus angle estimation. HVAngleEst comprises 1,382 X-ray images from 1,150 patients and includes comprehensive annotations, such as foot localization, hallux valgus angles, and line segments for each phalanx. This dataset enables fully automated, end-to-end hallux valgus angle estimation, reducing manual labor and eliminating evaluator bias.https://doi.org/10.1038/s41597-025-05261-9 |
| spellingShingle | Qiong Wang Dongdong Ji Junhu Wang Liang Liu Xinquan Yang Yan Zhang Jingqi Liang Peilong Liu Hongmou Zhao HVAngleEst: A Dataset for End-to-end Automated Hallux Valgus Angle Measurement from X-Ray Images Scientific Data |
| title | HVAngleEst: A Dataset for End-to-end Automated Hallux Valgus Angle Measurement from X-Ray Images |
| title_full | HVAngleEst: A Dataset for End-to-end Automated Hallux Valgus Angle Measurement from X-Ray Images |
| title_fullStr | HVAngleEst: A Dataset for End-to-end Automated Hallux Valgus Angle Measurement from X-Ray Images |
| title_full_unstemmed | HVAngleEst: A Dataset for End-to-end Automated Hallux Valgus Angle Measurement from X-Ray Images |
| title_short | HVAngleEst: A Dataset for End-to-end Automated Hallux Valgus Angle Measurement from X-Ray Images |
| title_sort | hvangleest a dataset for end to end automated hallux valgus angle measurement from x ray images |
| url | https://doi.org/10.1038/s41597-025-05261-9 |
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