ArticleLa Radiologia medica2020
Automated vertebrae localization and identification by decision forests and image-based refinement on real-world CT data.
Article in La Radiologia medica, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
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Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Artificial Intelligence and Computer Vision in Low Back Pain: A Systematic Review.International journal of environmental research and public health · 2021Pooled it
- AI-Driven Bone and Marrow Segmentation on FLT-PET/CT: Technical Multi-organ Validation in AML and HCT.Research square · 2026Article
- The Application of Artificial Intelligence in Spine Surgery: A Scoping Review.Journal of the American Academy of Orthopaedic Surgeons. Global research & reviews · 2025Article
- External validation of SpineNetV2 on a comprehensive set of radiological features for grading lumbosacral disc pathologies.North American Spine Society journal · 2024Article
- Using Artificial Intelligence to Predict the Development of Kyphosis Disease: A Systematic Review.Cureus · 2023Review
- Imaging of metabolic and overload disorders in tissues and organs.Japanese journal of radiology · 2023Review
- Lumbar spine segmentation method based on deep learning.Journal of applied clinical medical physics · 2023Article
- The promise and limitations of artificial intelligence in musculoskeletal imaging.Frontiers in radiology · 2023Review
- Current Applications of Machine Learning in Spine: From Clinical View.Global spine journal · 2022Review
- Artificial intelligence and spine imaging: limitations, regulatory issues and future direction.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 · 2022Review
- Artificial intelligence in spine care: current applications and future utility.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 · 2022Review
- Radiomics as a New Frontier of Imaging for Cancer Prognosis: A Narrative Review.Diagnostics (Basel, Switzerland) · 2021Review
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
purposeDevelopment of a fully automatic algorithm for the automatic localization and identification of vertebral bodies in computed tomography (CT). MATERIALS AND
methodsThis algorithm was developed using a dataset based on real-world data of 232 thoraco-abdominopelvic CT scans retrospectively collected. In order to achieve an accurate solution, a two-stage automated method was developed: decision forests for a rough prediction of vertebral bodies position, and morphological image processing techniques to refine the previous detection by locating the position of the spinal canal.
resultsThe mean distance error between the predicted vertebrae centroid position and truth was 13.7 mm. The identification rate was 79.6% on the thoracic region and of 74.8% on the lumbar segment.
conclusionThe algorithm provides a new method to detect and identify vertebral bodies from arbitrary field-of-view body CT scans.
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Registered trials
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