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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Current development and prospects of deep learning in spine image analysis: a literature review
Biao Qu, Jianpeng Cao, Chen Qian, et al.
Quantitative Imaging in Medicine and Surgery (2022) Vol. 12, Iss. 6, pp. 3454-3479
Open Access | Times Cited: 29

Showing 1-25 of 29 citing articles:

An update on animal models of intervertebral disc degeneration and low back pain: Exploring the potential of artificial intelligence to improve research analysis and development of prospective therapeutics
Mauro Alini, Ashish D. Diwan, W. Mark Erwin, et al.
JOR Spine (2023) Vol. 6, Iss. 1
Open Access | Times Cited: 28
Differential diagnosis of benign and malignant vertebral compression fractures: Comparison and correlation of radiomics and deep learning frameworks based on spinal CT and clinical characteristics
Shuo Duan, Yichun Hua, Guanmei Cao, et al.
European Journal of Radiology (2023) Vol. 165, pp. 110899-110899
Closed Access | Times Cited: 17
Emerging trends and research foci of deep learning in spine: bibliometric and visualization study
Kai Chen, Xiao Zhai, Sheng Wang, et al.
Neurosurgical Review (2023) Vol. 46, Iss. 1
Open Access | Times Cited: 14
SymTC: A symbiotic Transformer-CNN net for instance segmentation of lumbar spine MRI
Jiasong Chen, Linchen Qian, Linhai Ma, et al.
Computers in Biology and Medicine (2024) Vol. 179, pp. 108795-108795
Open Access | Times Cited: 3
A State-of-the-Art Survey of Deep Learning for Lumbar Spine Image Analysis: X-Ray, CT, and MRI
Ruyi Zhang
AI medicine. (2024), pp. 3-3
Closed Access | Times Cited: 2
The potential for different computed tomography-based machine learning networks to automatically segment and differentiate pelvic and sacral osteosarcoma from Ewing’s sarcoma
Ping Yin, Wenjia Wang, Sicong Wang, et al.
Quantitative Imaging in Medicine and Surgery (2023) Vol. 13, Iss. 5, pp. 3174-3184
Open Access | Times Cited: 6
Differentiating spinal pathologies by deep learning approach
Oz Haim, Ariel Agur, Segev Gabay, et al.
The Spine Journal (2023) Vol. 24, Iss. 2, pp. 297-303
Closed Access | Times Cited: 6
Development of a Deep-Learning Model for Diagnosing Lumbar Spinal Stenosis Based on CT Images
Kaiyu Li, Junjie Weng, Hua-Lin Li, et al.
Spine (2023) Vol. 49, Iss. 12, pp. 884-891
Closed Access | Times Cited: 5
Artificial intelligence: a new cutting-edge tool in spine surgery
Guna Pratheep Kalanjiyam, T. Chandramohan, M J Shankar Raman, et al.
Asian Spine Journal (2024) Vol. 18, Iss. 3, pp. 458-471
Open Access | Times Cited: 1
Automated measurement of lumbar pedicle screw parameters using deep learning algorithm on preoperative CT scans
Qian Zhang, Fanfan Zhao, Zihan Zhang, et al.
Journal of bone oncology (2024) Vol. 47, pp. 100627-100627
Open Access | Times Cited: 1
Automated Association for Osteosynthesis Foundation and Orthopedic Trauma Association classification of pelvic fractures on pelvic radiographs using deep learning
Seung Hwan Lee, J.W.J. Jeon, Gil Jae Lee, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 1
Deep Learning-Based Approaches for Classifying Foraminal Stenosis Using Cervical Spine Radiographs
Jiho Park, Jaejun Yang, Sehan Park, et al.
Electronics (2022) Vol. 12, Iss. 1, pp. 195-195
Open Access | Times Cited: 5
Development and multi‐institutional validation of a convolutional neural network to detect vertebral body mis‐alignments in 2D x‐ray setup images
Rachel Petragallo, Pascal Bertram, Per H. Halvorsen, et al.
Medical Physics (2023) Vol. 50, Iss. 5, pp. 2662-2671
Closed Access | Times Cited: 2
Deep Q-learning to globally optimize a k-D parameter search for medical imaging
Hongmei Zhang, Songshi Liang, Luke A. Matkovic, et al.
Quantitative Imaging in Medicine and Surgery (2023) Vol. 13, Iss. 8, pp. 4879-4896
Open Access | Times Cited: 2
Deep learning-driven diagnosis of multi-type vertebra diseases based on computed tomography images
Yongjie Wang, Feng Su, Lu Qian, et al.
Quantitative Imaging in Medicine and Surgery (2023) Vol. 14, Iss. 1, pp. 800-813
Open Access | Times Cited: 2
Automated detection of vertebral body misalignments in orthogonal kV and MV guided radiotherapy: application to a comprehensive retrospective dataset
John Charters, Dishane C. Luximon, Rachel Petragallo, et al.
Biomedical Physics & Engineering Express (2024) Vol. 10, Iss. 2, pp. 025039-025039
Open Access
Exploring Neighbor Spatial Relationships for Enhanced Lumbar Vertebrae Detection in X-ray Images
Yu Zeng, Kun Wang, Lai Dai, et al.
Electronics (2024) Vol. 13, Iss. 11, pp. 2137-2137
Open Access
Application of metal artifact reduction algorithm in reducing metal artifacts in post-surgery pediatric low radiation dose spine computed tomography (CT) images
Jihang Sun, Haoyan Li, Tong Yu, et al.
Quantitative Imaging in Medicine and Surgery (2024) Vol. 14, Iss. 7, pp. 4648-4658
Open Access
A systematic review of deep learning-based spinal bone lesion detection in medical images
Bianca Teodorescu, Leonard Gilberg, Philip William Melton, et al.
Acta Radiologica (2024) Vol. 65, Iss. 9, pp. 1115-1125
Closed Access
Evaluating the Status and Promising Potential of Robotic Spinal Surgery Systems
Xiang Li, Jiasheng Chen, Ben Wang, et al.
Orthopaedic Surgery (2024) Vol. 16, Iss. 11, pp. 2620-2632
Open Access
Deep learning model for automated diagnosis of degenerative cervical spondylosis and altered spinal cord signal on MRI
Aric Lee, Junran Wu, Changshuo Liu, et al.
The Spine Journal (2024)
Closed Access
Computer-Assisted Analysis of Myelography
Rhythm Kulshrestha
Advances in medical technologies and clinical practice book series (2024), pp. 147-166
Closed Access
Application and Prospects of Deep Learning Technology in Fracture Diagnosis
Jiayao Zhang, Jiaming Yang, Xin-meng Wang, et al.
Current Medical Science (2024)
Closed Access
Deep learning models for MRI-based clinical decision support in cervical spine degenerative diseases
Kaiyu Li, Zhongxin Lu, Yuhan Tian, et al.
Frontiers in Neuroscience (2024) Vol. 18
Open Access
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