ArticleRadiology. Artificial intelligence2022
Vertebral Deformity Measurements at MRI, CT, and Radiography Using Deep Learning.
Article in Radiology. Artificial intelligence, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Geometric plane alignment as a methodological requirement for accurate angular measurement in three-dimensional craniofacial imaging.BMC oral health · 2026Article
- Quantification and classification of lumbar disc herniation on axial magnetic resonance images using deep learning models.La Radiologia medica · 2025Article
- An automated algorithm for quantitative morphometry of thoracic and lumbar vertebral bodies in lateral radiographs.JBMR plus · 2025Article
- Normative vertebral deformity measurements in a clinically relevant population using magnetic resonance imaging.World journal of radiology · 2024Article
- 3D U-Net Neural Network Architecture-Assisted LDCT to Acquire Vertebral Morphology Parameters: A Vertebral Morphology Comprehensive Analysis in a Chinese Population.Calcified tissue international · 2024Article
- An Automated Vertebrae Localization, Segmentation, and Osteoporotic Compression Fracture Detection Pipeline for Computed Tomographic Imaging.Journal of imaging informatics in medicine · 2024Article
- Applications of Artificial Intelligence and Machine Learning in Spine MRI.Bioengineering (Basel, Switzerland) · 2024Review
- Artificial Intelligence in Spinal Imaging and Patient Care: A Review of Recent Advances.Neurospine · 2024Article
- Conquering the Cobb Angle: A Deep Learning Algorithm for Automated, Hardware-Invariant Measurement of Cobb Angle on Radiographs in Patients with Scoliosis.Radiology. Artificial intelligence · 2023Article
- Automatic vertebral fracture and three-column injury diagnosis with fracture visualization by a multi-scale attention-guided network.Medical & biological engineering & computing · 2023Article
- Performance of a deep convolutional neural network for MRI-based vertebral body measurements and insufficiency fracture detection.European radiology · 2023Article
- Localization and Edge-Based Segmentation of Lumbar Spine Vertebrae to Identify the Deformities Using Deep Learning Models.Sensors (Basel, Switzerland) · 2022Article
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Authors and funding
16 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeTo construct and evaluate the efficacy of a deep learning system to rapidly and automatically locate six vertebral landmarks, which are used to measure vertebral body heights, and to output spine angle measurements (lumbar lordosis angles [LLAs]) across multiple modalities. MATERIALS AND
methodsIn this retrospective study, MR (
resultsOn the holdout testing dataset (225 MR, 27 CT, and 97 radiographic images), the network was able to measure vertebral heights (mean height percentage of error ± 1 standard deviation: MR images, 1.5% ± 0.3; CT scans, 1.9% ± 0.2; radiographs, 1.7% ± 0.4) and produce other measures such as the LLA (mean absolute error: MR images, 2.90°; CT scans, 2.26°; radiographs, 3.60°) in less than 1.7 seconds across MR, CT, and radiographic imaging studies.
conclusionThe developed network was able to rapidly measure morphometric quantities in vertebral bodies and output LLAs across multiple modalities.
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