Vertebra-Focused Landmark Detection for Scoliosis Assessment
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Abstract (arXiv)
Adolescent idiopathic scoliosis (AIS) is a lifetime disease that arises in children. Accurate estimation of Cobb angles of the scoliosis is essential for clinicians to make diagnosis and treatment decisions. The Cobb angles are measured according to the vertebrae landmarks. Existing regression-based methods for the vertebra landmark detection typically suffer from large dense mapping parameters and inaccurate landmark localization. The segmentation-based methods tend to predict connected or corrupted vertebra masks. In this paper, we propose a novel vertebra-focused landmark detection method. Our model first localizes the vertebra centers, based on which it then traces the four corner landmarks of the vertebra through the learned corner offset. In this way, our method is able to keep the order of the landmarks. The comparison results demonstrate the merits of our method in both Cobb angle measurement and landmark detection on low-contrast and ambiguous X-ray images. Code is available at: urlhttps://github.com/yijingru/Vertebra-Landmark-Detection.
Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). First posted on arXiv 9 Jan 2020.
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Citing papers per year: 2021: 1; 2022: 4; 2023: 1; 2024: 3; 2025: 2.
11 papers.
- 2022Seg4Reg+: Consistency Learning between Spine Segmentation and Cobb Angle Regressioncited by 11
- 2022Morphology-Aware Interactive Keypoint Estimationcited by 4
- 2021Scalable Semi-supervised Landmark Localization for X-ray Images using Few-shot Deep Adaptive Graphcited by 3
- 2022Accurate Scoliosis Vertebral Landmark Localization on X-ray Images via Shape-constrained Multi-stage Cascaded CNNscited by 3
- 2024CABLD: Contrast-Agnostic Brain Landmark Detection with Consistency-Based Regularizationcited by 2
- 2022Automating Cobb Angle Measurement for Adolescent Idiopathic Scoliosis using Instance Segmentationcited by 1
- 2023Topology-inspired Cross-domain Network for Developmental Cervical Stenosis Quantificationcited by 0
- 2024Deep learning automates Cobb angle measurement compared with multi-expert observerscited by 0
- 2024CurvNet: Latent Contour Representation and Iterative Data Engine for Curvature Angle Estimationcited by 0
- 2025VerteNet -- A Multi-Context Hybrid CNN Transformer for Accurate Vertebral Landmark Localization in Lateral Spine DXA Imagescited by 0
- 2025Submillimeter-Accurate 3D Lumbar Spine Reconstruction from Biplanar X-Ray Images: Incorporating a Multi-Task Network and Landmark-Weighted Losscited by 0
- 2025Submillimeter-Accurate 3D Lumbar Spine Reconstruction from Biplanar X-Ray Images: Incorporating a Multi-Task Network and Landmark-Weighted Loss18 Mar 2025
- 2025VerteNet -- A Multi-Context Hybrid CNN Transformer for Accurate Vertebral Landmark Localization in Lateral Spine DXA Images4 Feb 2025
- 2024CABLD: Contrast-Agnostic Brain Landmark Detection with Consistency-Based Regularization26 Nov 2024
- 2024CurvNet: Latent Contour Representation and Iterative Data Engine for Curvature Angle Estimation19 Nov 2024
- 2024Deep learning automates Cobb angle measurement compared with multi-expert observers18 Mar 2024
- 2023Topology-inspired Cross-domain Network for Developmental Cervical Stenosis Quantification13 Sep 2023
- 2022Automating Cobb Angle Measurement for Adolescent Idiopathic Scoliosis using Instance Segmentation25 Nov 2022
- 2022Morphology-Aware Interactive Keypoint Estimation15 Sep 2022
- 2022Seg4Reg+: Consistency Learning between Spine Segmentation and Cobb Angle Regression26 Aug 2022
- 2022Accurate Scoliosis Vertebral Landmark Localization on X-ray Images via Shape-constrained Multi-stage Cascaded CNNs5 Jun 2022
- 2021Scalable Semi-supervised Landmark Localization for X-ray Images using Few-shot Deep Adaptive Graph29 Apr 2021