ArticleJournal of clinical medicine2023
Prediction of Cobb Angle Using Deep Learning Algorithm with Three-Dimensional Depth Sensor Considering the Influence of Garment in Idiopathic Scoliosis.
Article in Journal of clinical medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 18 citations in OpenAlex.
- [Thinking, evaluating, and replenishing the fibrinogen hemostatic strategy in neurosurgery].Revista medica del Instituto Mexicano del Seguro Social · 2026Review
- Automatic radiation-free evaluation of Cobb angle for spinal curvature based on fringe projection profilometry and deep learning technology.Spine deformity · 2026Article
- Automated Measurement of Occipito-Axial Angle on Cervical Radiographs Using a Deep Learning Object Detection Model: A Proof-of-Concept Study.Neurospine · 2026Article
- Enhanced Vision Transformer with Custom Attention Mechanism for Automated Idiopathic Scoliosis Classification.Journal of imaging informatics in medicine · 2026Article
- Automated CT dataset generation as a novel concept for verification of backshape-to-spine approach and Cobb Angle Estimation.PloS one · 2026Article
- Wearable Devices in Scoliosis Treatment: A Scoping Review of Innovations and Challenges.Bioengineering (Basel, Switzerland) · 2025Review
- Noninvasive estimation of internal spinal alignment in patients with adolescent idiopathic scoliosis using PCdare and back shape asymmetry.Scientific reports · 2025Article
- PCdare software registers 3D back surface with biplanar radiographs: application to patients with scoliosis.Frontiers in digital health · 2025Article
- Automated measurement of lumbar pedicle screw parameters using deep learning algorithm on preoperative CT scans.Journal of bone oncology · 2024Article
- Explainable Deep-Learning-Based Gait Analysis of Hip-Knee Cyclogram for the Prediction of Adolescent Idiopathic Scoliosis Progression.Sensors (Basel, Switzerland) · 2024Article
- Minimal Required Resolution to Capture the 3D Shape of the Human Back-A Practical Approach.Sensors (Basel, Switzerland) · 2023Article
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Authors and funding
13 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Adolescent idiopathic scoliosis (AIS) is the most common pediatric spinal deformity. Early detection of deformity and timely intervention, such as brace treatment, can help inhibit progressive changes. A three-dimensional (3D) depth-sensor imaging system with a convolutional neural network was previously developed to predict the Cobb angle. The purpose of the present study was to (1) evaluate the performance of the deep learning algorithm (DLA) in predicting the Cobb angle and (2) assess the predictive ability depending on the presence or absence of clothing in a prospective analysis. We included 100 subjects with suspected AIS. The correlation coefficient between the actual and predicted Cobb angles was 0.87, and the mean absolute error and root mean square error were 4.7° and 6.0°, respectively, for Adam's forward bending without underwear. There were no significant differences in the correlation coefficients between the groups with and without underwear in the forward-bending posture. The performance of the DLA with a 3D depth sensor was validated using an independent external validation dataset. Because the psychological burden of children and adolescents on naked body imaging is an unignorable problem, scoliosis examination with underwear is a valuable alternative in clinics or schools.
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