ArticleRadiology. Artificial intelligence2023
Conquering the Cobb Angle: A Deep Learning Algorithm for Automated, Hardware-Invariant Measurement of Cobb Angle on Radiographs in Patients with Scoliosis.
Article in Radiology. Artificial intelligence, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed.
- Can General-purpose Multimodal AI Reliably Measure Cobb Angles? A Head-to-head Diagnostic Agreement Study of GPT-5.1 and Gemini 3.1 Pro in Adolescent Idiopathic Scoliosis.Journal of imaging informatics in medicine · 2026Article
- Algorithmic fairness reporting in artificial intelligence for spinal deformity: a systematic review.Spine deformity · 2026Review
- Dual-stage anatomical perception and reasoning framework for automated cobb angle estimation.Medical & biological engineering & computing · 2026Article
- Principles Underlying Surgical Decision-Making in Lowest-Instrumented Vertebra Level Selection of Adolescent Idiopathic Scoliosis: From Traditional Landmarks to Emerging Predictive Models-A Narrative Review.Journal of clinical medicine · 2026Review
- Comparative Evaluation of Feature Selection Strategies for ICU Mortality Prediction Using Chest Radiographic, Radiomic, and Demographic Features.Diagnostics (Basel, Switzerland) · 2026Article
- Development and validation of a deep learning model for radiographic classification of pediatric femoral neck fractures.Journal of orthopaedics and traumatology : official journal of the Italian Society of Orthopaedics and Traumatology · 2026Article
- Deep learning based vertebra localization and Cobb angle estimation using x-ray images.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2026Article
- Deep-Learning System for Automatic Measurement of the Femorotibial Rotational Angle on Lower-Extremity Computed Tomography.Journal of imaging informatics in medicine · 2026Article
- Lower calcium/phosphorus ratio is associated with the severity of deformity in patients with scoliosis.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2026Article
- Deep learning based screening and regular assessment of adolescent idiopathic scoliosis using wearable IMU sensors.Frontiers in bioengineering and biotechnology · 2026Article
- Reference ranges and dimensional structure of upper body posture parameters in adults: a cross-sectional study.Frontiers in rehabilitation sciences · 2026Article
- Interpretable automated cobb angle measurement in adolescent idiopathic scoliosis using a lightweight keypoint-to-geometry network: cross-center external validation.Frontiers in medicine · 2026Article
- Evaluation of AI Performance in Spinal Radiographic Measurements Compared to Radiologists: A Study of Accuracy and Efficiency.Journal of imaging · 2025Article
- Convolutional Neural Network-Based Approach for Cobb Angle Measurement Using Mask R-CNN.Diagnostics (Basel, Switzerland) · 2025Article
- Deep learning automates Cobb angle measurement compared with multi-expert observers.BJR artificial intelligence · 2025Article
- Radiographic Analysis of Scoliosis Using Convolutional Neural Network in Clinical Practice.Journal of the Korean Society of Radiology · 2024Article
- Development and validation of AI-based automatic measurement of coronal Cobb angles in degenerative scoliosis using sagittal lumbar MRI.European radiology · 2024Article
- Comparison of three artificial intelligence algorithms for automatic cobb angle measurement using teaching data specific to three disease groups.Scientific reports · 2024Article
- Artificial Intelligence in Spinal Imaging and Patient Care: A Review of Recent Advances.Neurospine · 2024Article
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14 authors.
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Abstract
Scoliosis is a disease estimated to affect more than 8% of adults in the United States. It is diagnosed with use of radiography by means of manual measurement of the angle between maximally tilted vertebrae on a radiograph (ie, the Cobb angle). However, these measurements are time-consuming, limiting their use in scoliosis surgical planning and postoperative monitoring. In this retrospective study, a pipeline (using the SpineTK architecture) was developed that was trained, validated, and tested on 1310 anterior-posterior images obtained with a low-dose stereoradiographic scanning system and radiographs obtained in patients with suspected scoliosis to automatically measure Cobb angles. The images were obtained at six centers (2005-2020). The algorithm measured Cobb angles on hold-out internal (
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