mlsanityData to 7 Oct 2026

Intelligent Scoliosis Screening and Diagnosis: A Survey

arXiv 2310.08756 ↗First posted 12 Oct 2023eess.IV cs.CVcited by 0

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Abstract (arXiv)

Scoliosis is a three-dimensional spinal deformity, which may lead to abnormal morphologies, such as thoracic deformity, and pelvic tilt. Severe patients may suffer from nerve damage and urinary abnormalities. At present, the number of scoliosis patients in primary and secondary schools has exceeded five million in China, the incidence rate is about 3% to 5% which is growing every year. The research on scoliosis, therefore, has important clinical value. This paper systematically introduces computer-assisted scoliosis screening and diagnosis as well as analyzes the advantages and limitations of different algorithm models in the current issue field. Moreover, the paper also discusses the current development bottlenecks in this field and looks forward to future development trends.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 9 of its 37 references that are in the map. First posted on arXiv 12 Oct 2023.

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9 of 37 references.

References · 9

  1. 2017Attention Is All You Needcited by 59,932
  2. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
  3. 2016Image-to-Image Translation with Conditional Adversarial Networkscited by 4,510
  4. 2019High-Resolution Representations for Labeling Pixels and Regionscited by 211
  5. 2020VerSe: A Vertebrae Labelling and Segmentation Benchmark for Multi-detector CT Imagescited by 111
  6. 2019Integrating Spatial Configuration into Heatmap Regression Based CNNs for Landmark Localizationcited by 77
  7. 2018Iterative fully convolutional neural networks for automatic vertebra segmentation and identificationcited by 25
  8. 2018Generating Synthetic X-ray Images of a Person from the Surface Geometrycited by 9
  9. 2019Detection of vertebral fractures in CT using 3D Convolutional Neural Networkscited by 9

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