Compression Fractures Detection on CT
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Abstract (arXiv)
The presence of a vertebral compression fracture is highly indicative of osteoporosis and represents the single most robust predictor for development of a second osteoporotic fracture in the spine or elsewhere. Less than one third of vertebral compression fractures are diagnosed clinically. We present an automated method for detecting spine compression fractures in Computed Tomography (CT) scans. The algorithm is composed of three processes. First, the spinal column is segmented and sagittal patches are extracted. The patches are then binary classified using a Convolutional Neural Network (CNN). Finally a Recurrent Neural Network (RNN) is utilized to predict whether a vertebral fracture is present in the series of patches.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). First posted on arXiv 6 Jun 2017.
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Citing papers per year: 2022: 2; 2023: 1; 2024: 2.
5 papers.
- 2022Interpretable Vertebral Fracture Quantification via Anchor-Free Landmarks Localizationcited by 8
- 2022Interpretable Vertebral Fracture Diagnosiscited by 4
- 2023Semantic Latent Space Regression of Diffusion Autoencoders for Vertebral Fracture Gradingcited by 2
- 2024Enhancing Interpretability of Vertebrae Fracture Grading using Human-interpretable Prototypescited by 0
- 2024An Intrinsically Explainable Approach to Detecting Vertebral Compression Fractures in CT Scans via Neurosymbolic Modelingcited by 0
- 2024An Intrinsically Explainable Approach to Detecting Vertebral Compression Fractures in CT Scans via Neurosymbolic Modeling23 Dec 2024
- 2024Enhancing Interpretability of Vertebrae Fracture Grading using Human-interpretable Prototypes3 Apr 2024
- 2023Semantic Latent Space Regression of Diffusion Autoencoders for Vertebral Fracture Grading21 Mar 2023
- 2022Interpretable Vertebral Fracture Quantification via Anchor-Free Landmarks Localization14 Apr 2022
- 2022Interpretable Vertebral Fracture Diagnosis30 Mar 2022