MGScoliosis: Multi-grained scoliosis detection with joint or…

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2024
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Work Details
  • DOI 10.1016/j.aej.2024.10.066
  • OpenAlex ID W4403731385
  • Type Article
  • Language EN
  • Published 24 Oct 2024
  • Volume 111
  • Pages 329–340
  • Source Alexandria Engineering Journal
  • Publisher Elsevier BV
  • FWCI 0.63
  • Countries 1
  • Institutions 7
  • Added 10 Oct 2025
  • Updated 16 Oct 2026
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MGScoliosis: Multi-grained scoliosis detection with joint ordinal regression from natural image

Article 2024 EN Gold

Scoliosis is among the most prevalent diseases affecting teenagers. However, traditional scoliosis screening methods often resort to physical examination or radiographic imaging. The two ways both rely on experts with high costs, which are not suitable for wide-range screening. Besides, estimating Cobb angle level only using natural images are challenging. To tackle these issues, we propose a mult…

6

Citations

62

References

7

Authors

0.63

FWCI

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Authors & Affiliations
7 authors
#AuthorInstitutionsORCID
1 Xiaojia Zhu University of Science and Tech… (CN) Xuzhou Medical College (CN) +2
2 Rui Chen China University of Mining and… (CN)
3 Zhiwen Shao University of Science and Tech… (CN) China University of Mining and… (CN)
4 Ming Zhang Xuzhou Medical College (CN) Xuzhou Central Hospital (CN) +1
5 Yuhu Dai University of Science and Tech… (CN) Sun Yat-sen University (CN) +1
6 Wenzhi Zhang University of Science and Tech… (CN)
7 Chuandong Lang Corresponding University of Science and Tech… (CN) Sun Yat-sen University (CN) +1

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