The DOI matches its Crossref record; 18 of the 18 references it cites were found in a registry or an index.
Automatic Lumbar Vertebrae Detection Based on Feature Fusion Deep Learning for Partial Occluded C-arm X-ray Images
Abstract
Automatic and accurate lumbar vertebrae detection is an essential step of image-guided minimally invasive spine surgery (IG-MISS). However, traditional methods still require human intervention due to the similarity of vertebrae, abnormal pathological conditions and uncertain imaging angle. In this paper, we present a novel convolutional neural network (CNN) model to automatically detect lumbar vertebrae for C-arm X-ray images. Training data is augmented by DRR and automatic segmentation of ROI is able to reduce the computational complexity. Furthermore, a feature fusion deep learning (FFDL) model is introduced to combine two types of features of lumbar vertebrae X-ray images, which uses sobel kernel and Gabor kernel to obtain the contour and texture of lumbar vertebrae, respectively. Comprehensive qualitative and quantitative experiments demonstrate that our proposed model performs more accurate in abnormal cases with pathologies and surgical implants in multi-angle views.
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“traditional DRR generation, e. g. as in [8,4], does not accurately model X-ray image formation”
From DeepDRR – A Catalyst for Machine Learning in Fluoroscopy-Guided Procedures (2018) · cites this paper as [4]
Citations
Cites
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Suzani, A., Seitel, A., Liu, Y., Fels, S., Rohling, R. N., & Abolmaesumi, P. (2015) · Lecture notes in computer science · doi:10.1007/978-3-319-24574-4_81 · Cited by 83
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Research works printed but not linked: 1
- wang, 2016, A preoperative planning algorithm based on dexterity and collaborationspace for the robot-assisted minimally invasive surgery, Robot, 38, 208
Cited by
Sorted by citations
DeepDRR – A Catalyst for Machine Learning in Fluoroscopy-Guided Procedures
Unberath, M., Zaech, J.-N., Lee, S. C., Bier, B., Fotouhi, J., Armand, M., & Navab, N. (2018) · Lecture Notes in Computer Science · doi:10.1007/978-3-030-00937-3_12 · Cited by 145
“A promising approach to tackling the above challenges is in silico fluoroscopy generation from diagnostic 3D CT, most commonly referred to as digitally re-constructed radiographs (DRRs) [4,5].”
Background
Metadata
- Authors
- Li, Y., Liang, W., Zhang, Y., An, H., & Tan, J.
- Affiliations
- University of Chinese Academy of Sciences (CN)
- Chinese Academy of Sciences (CN)
- University of Tennessee at Knoxville (US)
- Venue
- 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
- Publisher
- IEEE
- Published
- 2016-08
- Volume
- 2016
- Pages
- 647-650
- ISSN
- 2375-7477 (ISSN-L)
- OpenAlex
- W2534847668
- Cited by
- 27
- References
- 18
- Citations by year
- 2026: 1 · 2025: 3 · 2024: 2 · 2023: 2 · 2022: 4 · 2021: 3 · 2020: 4 · 2019: 2 · 2018: 3 · 2017: 3
- FWCI
- 5.34
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (publishedVersion)
- PubMed (publishedVersion)
- SIA OpenIR (Chinese Academy of Sciences) (submittedVersion)
- Funders
- National Natural Science Foundation of China
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › Medical Imaging and Analysis
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Medical Image Segmentation Techniques
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Neural Network Applications
- Keywords
- partial occlusion, region of interest segmentation, Sobel edge detection, Gabor texture features, surgical implants, multi-angle imaging
- MeSH terms
- Adult, Aged, Algorithms, Automation, Humans, Image Processing, Computer-Assisted, Lumbar Vertebrae, Middle Aged, Tomography, X-Ray Computed
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- CoChat. (2026). Citation check: Automatic Lumbar Vertebrae Detection Based on Feature Fusion Deep Learning for Partial Occluded C-arm X-ray Images. https://app.cochat.ai/papers/10.1109/embc.2016.7590785
- The paper
- Li, Y., Liang, W., Zhang, Y., An, H., & Tan, J. (2016). Automatic Lumbar Vertebrae Detection Based on Feature Fusion Deep Learning for Partial Occluded C-arm X-ray Images. 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). https://doi.org/10.1109/embc.2016.7590785
