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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:

Review of Deep Learning Based Automatic Segmentation for Lung Cancer Radiotherapy
Xi Liu, Kai-Wen Li, Ruijie Yang, et al.
Frontiers in Oncology (2021) Vol. 11
Open Access | Times Cited: 77

Showing 1-25 of 77 citing articles:

Artificial intelligence and machine learning in cancer imaging
Dow‐Mu Koh, Nikolaos Papanikolaou, Ulrich Bick, et al.
Communications Medicine (2022) Vol. 2, Iss. 1
Open Access | Times Cited: 176
Medical Images Segmentation for Lung Cancer Diagnosis Based on Deep Learning Architectures
Yahia Said, Ahmed A. Alsheikhy, Tawfeeq Shawly, et al.
Diagnostics (2023) Vol. 13, Iss. 3, pp. 546-546
Open Access | Times Cited: 52
Revolutionizing radiation therapy: the role of AI in clinical practice
Mariko Kawamura, Takeshi Kamomae, Masahiro Yanagawa, et al.
Journal of Radiation Research (2023) Vol. 65, Iss. 1, pp. 1-9
Open Access | Times Cited: 26
Deep learning for lungs cancer detection: a review
Rabia Javed, Tahir Abbas, Ali Haider Khan, et al.
Artificial Intelligence Review (2024) Vol. 57, Iss. 8
Open Access | Times Cited: 12
Review of Deep Learning Based Autosegmentation for Clinical Target Volume: Current Status and Future Directions
Thomas Matoska, Mira A. Patel, Hefei Liu, et al.
Advances in Radiation Oncology (2024) Vol. 9, Iss. 5, pp. 101470-101470
Open Access | Times Cited: 11
Deep learning for autosegmentation for radiotherapy treatment planning: State-of-the-art and novel perspectives
Ayhan Can Erdur, Daniel Rusche, Daniel Scholz, et al.
Strahlentherapie und Onkologie (2024)
Open Access | Times Cited: 11
Recent Applications of Artificial Intelligence in Radiotherapy: Where We Are and Beyond
Miriam Santoro, Silvia Strolin, Giulia Paolani, et al.
Applied Sciences (2022) Vol. 12, Iss. 7, pp. 3223-3223
Open Access | Times Cited: 31
Automatic Segmentation with Deep Learning in Radiotherapy
Lars Johannes Isaksson, Paul Summers, Federico Mastroleo, et al.
Cancers (2023) Vol. 15, Iss. 17, pp. 4389-4389
Open Access | Times Cited: 20
A Thorough Review of the Clinical Applications of Artificial Intelligence in Lung Cancer
Serafeim‐Chrysovalantis Kotoulas, Dionysios Spyratos, Κonstantinos Porpodis, et al.
Cancers (2025) Vol. 17, Iss. 5, pp. 882-882
Open Access
Intelligent oncology: The convergence of artificial intelligence and oncology
Bo Lin, Zhibo Tan, Yaqi Mo, et al.
Journal of the National Cancer Center (2022) Vol. 3, Iss. 1, pp. 83-91
Open Access | Times Cited: 25
Deep learning in CT image segmentation of cervical cancer: a systematic review and meta-analysis
Chongze Yang, Lan-hui Qin, Yu-en Xie, et al.
Radiation Oncology (2022) Vol. 17, Iss. 1
Open Access | Times Cited: 24
Automated Tumor Segmentation in Radiotherapy
Ricky R. Savjani, Michael Lauria, Supratik Bose, et al.
Seminars in Radiation Oncology (2022) Vol. 32, Iss. 4, pp. 319-329
Open Access | Times Cited: 23
Lung-RetinaNet: Lung Cancer Detection Using a RetinaNet With Multi-Scale Feature Fusion and Context Module
Rabbia Mahum, AbdulMalik S. Al‐Salman
IEEE Access (2023) Vol. 11, pp. 53850-53861
Open Access | Times Cited: 15
A deep learning‐based framework (Co‐ReTr) for auto‐segmentation of non‐small cell‐lung cancer in computed tomography images
Tenzin Kunkyab, Zhila Bahrami, Heqing Zhang, et al.
Journal of Applied Clinical Medical Physics (2024) Vol. 25, Iss. 3
Open Access | Times Cited: 4
Evaluating deep learning auto-contouring for lung radiation therapy: A review of accuracy, variability, efficiency and dose, in target volumes and organs at risk
Kathryn Moran, Claire Poole, Sarah Barrett
Physics and Imaging in Radiation Oncology (2025) Vol. 33, pp. 100736-100736
Open Access
Medical imaging and artificial intelligence in radiotherapy of malignant tumors
G. Panshin, Н. В. Нуднов
Medical Visualization (2025)
Closed Access
Cnidaria herd optimized fuzzy C-means clustering enabled deep learning model for lung nodule detection
Roshan Rao, Agam Das Goswami
Frontiers in Physiology (2025) Vol. 16
Open Access
Deep learning model for automatic contouring of cardiovascular substructures on radiotherapy planning CT images: Dosimetric validation and reader study based clinical acceptability testing
Miguel Garrett Fernandes, Johan Bussink, Barbara Stam, et al.
Radiotherapy and Oncology (2021) Vol. 165, pp. 52-59
Open Access | Times Cited: 27
The effect of convolutional neural network architectures on phase segmentation of composite material X-ray micrographs
Pedro Galvez-Hernandez, James Kratz
Journal of Composite Materials (2023) Vol. 57, Iss. 18, pp. 2899-2918
Open Access | Times Cited: 11
Enhancing non-small cell lung cancer radiotherapy planning: A deep learning-based multi-modal fusion approach for accurate GTV segmentation
Shaik Ummay Atiya, N. V. K. Ramesh
Biomedical Signal Processing and Control (2024) Vol. 92, pp. 105987-105987
Closed Access | Times Cited: 3
FastSAM-3DSlicer: A 3D-Slicer Extension for 3D Volumetric Segment Anything Model with Uncertainty Quantification
Yiqing Shen, Xinyuan Shao, Blanca Inigo Romillo, et al.
Lecture notes in computer science (2024), pp. 1-9
Closed Access | Times Cited: 3
Deep Learning Model for Classifying Metastatic Epidural Spinal Cord Compression on MRI
James Thomas Patrick Decourcy Hallinan, Lei Zhu, Wenqiao Zhang, et al.
Frontiers in Oncology (2022) Vol. 12
Open Access | Times Cited: 18
Application of nnU-Net for Automatic Segmentation of Lung Lesions on CT Images and Its Implication for Radiomic Models
Matteo Ferrante, Lisa Rinaldi, Francesca Botta, et al.
Journal of Clinical Medicine (2022) Vol. 11, Iss. 24, pp. 7334-7334
Open Access | Times Cited: 16
Patient-specific neural networks for contour propagation in online adaptive radiotherapy
A. Smolders, Antony Lomax, DC Weber, et al.
Physics in Medicine and Biology (2023) Vol. 68, Iss. 9, pp. 095010-095010
Open Access | Times Cited: 10
Multi-task learning-based histologic subtype classification of non-small cell lung cancer
Kun Chen, Manning Wang, Zhijian Song
La radiologia medica (2023) Vol. 128, Iss. 5, pp. 537-543
Closed Access | Times Cited: 9
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