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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:

Generative models: an upcoming innovation in musculoskeletal radiology? A preliminary test in spine imaging
Fabio Galbusera, Tito Bassani, Gloria Casaroli, et al.
European Radiology Experimental (2018) Vol. 2, Iss. 1
Open Access | Times Cited: 43

Showing 1-25 of 43 citing articles:

A review on medical imaging synthesis using deep learning and its clinical applications
Tonghe Wang, Yang Lei, Yabo Fu, et al.
Journal of Applied Clinical Medical Physics (2020) Vol. 22, Iss. 1, pp. 11-36
Open Access | Times Cited: 212
AI applications in musculoskeletal imaging: a narrative review
Salvatore Gitto, Francesca Serpi, Domenico Albano, et al.
European Radiology Experimental (2024) Vol. 8, Iss. 1
Open Access | Times Cited: 21
Current applications and future directions of deep learning in musculoskeletal radiology
Pauley Chea, Jacob Mandell
Skeletal Radiology (2019) Vol. 49, Iss. 2, pp. 183-197
Closed Access | Times Cited: 110
Artificial intelligence applications in medical imaging: A review of the medical physics research in Italy
Michele Avanzo, M. Porzio, Leda Lorenzon, et al.
Physica Medica (2021) Vol. 83, pp. 221-241
Closed Access | Times Cited: 67
A practical guide to the development and deployment of deep learning models for the orthopedic surgeon: part II
Jacob F. Oeding, Riley J. Williams, Christopher L. Camp, et al.
Knee Surgery Sports Traumatology Arthroscopy (2023) Vol. 31, Iss. 5, pp. 1635-1643
Closed Access | Times Cited: 24
Artificial Intelligence in Musculoskeletal Imaging: Review of Current Literature, Challenges, and Trends
Anna Hirschmann, Joshy Cyriac, Bram Stieltjes, et al.
Seminars in Musculoskeletal Radiology (2019) Vol. 23, Iss. 03, pp. 304-311
Open Access | Times Cited: 65
Imaging in Spine Surgery: Current Concepts and Future Directions
Garrett K. Harada, Zakariah K. Siyaji, Sadaf Younis, et al.
Spine Surgery and Related Research (2020) Vol. 4, Iss. 2, pp. 99-110
Open Access | Times Cited: 51
Radiomic Machine Learning Classifiers in Spine Bone Tumors: A Multi-Software, Multi-Scanner Study
Vito Chianca, Renato Cuocolo, Salvatore Gitto, et al.
European Journal of Radiology (2021) Vol. 137, pp. 109586-109586
Open Access | Times Cited: 50
Artificial intelligence and treatment algorithms in spine surgery
Yann Philippe Charles, Vincent Lamas, Yves Ntilikina
Orthopaedics & Traumatology Surgery & Research (2022) Vol. 109, Iss. 1, pp. 103456-103456
Open Access | Times Cited: 29
Artificial Intelligence in Radiology
Muhammad Rehan Khan
Elsevier eBooks (2024), pp. 149-177
Closed Access | Times Cited: 7
Generative adversarial networks for spine imaging: A critical review of current applications
Konstantinos Vrettos, Emmanouil Koltsakis, Aristeidis Zibis, et al.
European Journal of Radiology (2024) Vol. 171, pp. 111313-111313
Closed Access | Times Cited: 6
Artificial Intelligence in Spinal Imaging: Current Status and Future Directions
Yangyang Cui, Jia Zhu, Zhili Duan, et al.
International Journal of Environmental Research and Public Health (2022) Vol. 19, Iss. 18, pp. 11708-11708
Open Access | Times Cited: 27
The promise and limitations of artificial intelligence in musculoskeletal imaging
Patrick Debs, Laura M. Fayad
Frontiers in Radiology (2023) Vol. 3
Open Access | Times Cited: 15
Denoising diffusion-based MRI to CT image translation enables automated spinal segmentation
Robert Graf, Joachim Schmitt, Sarah Schlaeger, et al.
European Radiology Experimental (2023) Vol. 7, Iss. 1
Open Access | Times Cited: 14
Feasibility of generating sagittal radiographs from coronal views using GAN-based deep learning framework in adolescent idiopathic scoliosis
Tito Bassani, Andrea Cina, Fabio Galbusera, et al.
European Radiology Experimental (2025) Vol. 9, Iss. 1
Open Access
Deep Generative Adversarial Networks: Applications in Musculoskeletal Imaging
YiRang Shin, Jaemoon Yang, Young Han Lee
Radiology Artificial Intelligence (2021) Vol. 3, Iss. 3, pp. e200157-e200157
Open Access | Times Cited: 26
The stability of oncologic MRI radiomic features and the potential role of deep learning: a review
Elisa Scalco, Giovanna Rizzo, Alfonso Mastropietro
Physics in Medicine and Biology (2022) Vol. 67, Iss. 9, pp. 09TR03-09TR03
Closed Access | Times Cited: 16
Utility of machine learning algorithms in degenerative cervical and lumbar spine disease: a systematic review
M. E. Stephens, Christen M. O’Neal, Alison M. Westrup, et al.
Neurosurgical Review (2021) Vol. 45, Iss. 2, pp. 965-978
Closed Access | Times Cited: 19
Convolutional Neural Networks in Spinal Magnetic Resonance Imaging: A Systematic Review
David Baur, Katharina Kroboth, C Heyde, et al.
World Neurosurgery (2022) Vol. 166, pp. 60-70
Closed Access | Times Cited: 14
Synthetic Contrasts in Musculoskeletal MRI
Tom Hilbert, Patrick Omoumi, Marcus Raudner, et al.
Investigative Radiology (2022) Vol. 58, Iss. 1, pp. 111-119
Closed Access | Times Cited: 14
Generating Virtual Short Tau Inversion Recovery (STIR) Images from T1- and T2-Weighted Images Using a Conditional Generative Adversarial Network in Spine Imaging
Johannes Haubold, Aydın Demircioğlu, Jens Theysohn, et al.
Diagnostics (2021) Vol. 11, Iss. 9, pp. 1542-1542
Open Access | Times Cited: 17
Artificial Intelligence in Radiology: Overview of Application Types, Design, and Challenges
Mana Moassefi, Shahriar Faghani, Bardia Khosravi, et al.
Seminars in Roentgenology (2023) Vol. 58, Iss. 2, pp. 170-177
Closed Access | Times Cited: 7
Conversion of T2-Weighted Magnetic Resonance Images of Cervical Spine Trauma to Short T1 Inversion Recovery (STIR) Images by Generative Adversarial Network
Atsushi Yunde, Satoshi Maki, Takeo Furuya, et al.
Cureus (2024)
Open Access | Times Cited: 2
Redefining precision: the current and future roles of artificial intelligence in spine surgery
Ryan Turlip, Harmon Khela, Mert Marcel Dagli, et al.
Artificial Intelligence Surgery (2024) Vol. 4, Iss. 4, pp. 324-30
Open Access | Times Cited: 2
Improving accelerated 3D imaging in MRI-guided radiotherapy for prostate cancer using a deep learning method
Ji Zhu, Xinyuan Chen, Yuxiang Liu, et al.
Radiation Oncology (2023) Vol. 18, Iss. 1
Open Access | Times Cited: 5
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