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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:

Comparison of deep learning networks for fully automated head and neck tumor delineation on multi-centric PET/CT images
Yiling Wang, Elia Lombardo, Lili Huang, et al.
Radiation Oncology (2024) Vol. 19, Iss. 1
Open Access | Times Cited: 9

Showing 9 citing articles:

HaN-Seg: The head and neck organ-at-risk CT and MR segmentation challenge
Gašper Podobnik, Bulat Ibragimov, Elias Tappeiner, et al.
Radiotherapy and Oncology (2024) Vol. 198, pp. 110410-110410
Open Access | Times Cited: 10
Gradient Map-Assisted Head and Neck Tumor Segmentation: A Pre-RT to Mid-RT Approach in MRI-Guided Radiotherapy
Jintao Ren, Kim Hochreuter, Mathis Rasmussen, et al.
Lecture notes in computer science (2025), pp. 36-49
Open Access
RadDeploy: A framework for integrating in-house developed software and artificial intelligence models seamlessly into radiotherapy workflows
Mathis Ersted Rasmussen, Casper Dueholm Vestergaard, Jesper Folsted Kallehauge, et al.
Physics and Imaging in Radiation Oncology (2024) Vol. 31, pp. 100607-100607
Open Access | Times Cited: 3
Enhancing the reliability of deep learning-based head and neck tumour segmentation using uncertainty estimation with multi-modal images
Jintao Ren, Jonas Teuwen, Jasper Nijkamp, et al.
Physics in Medicine and Biology (2024) Vol. 69, Iss. 16, pp. 165018-165018
Open Access | Times Cited: 2
Raddeploy: A Framework for Integrating In-House Developed Models Seamlessly into Radiotherapy Workflows
Mathis Ersted Rasmussen, Casper Dueholm Vestergaard, Jesper Folsted Kallehauge, et al.
(2024)
Closed Access
Deep learning with uncertainty estimation for automatic tumor segmentation in PET/CT of head and neck cancers: impact of model complexity, image processing and augmentation
Bao Ngoc Huynh, Aurora Rosvoll Groendahl, Oliver Tomić, et al.
Biomedical Physics & Engineering Express (2024) Vol. 10, Iss. 5, pp. 055038-055038
Closed Access
Perspectives for using artificial intelligence techniques in radiation therapy
Guillaume Landry, Christopher Kurz, Adrian Thummerer
The European Physical Journal Plus (2024) Vol. 139, Iss. 10
Closed Access
Imaging Tumor Metabolism and Its Heterogeneity: Special Focus on Radiomics and AI
László Papp, David Haberl, Boglarka Ecsedi, et al.
Interdisciplinary cancer research (2024)
Closed Access
Implementation of Automatic Segmentation Framework as Preprocessing Step for Radiomics Analysis of Lung Anatomical Districts
Alessandro Stefano, Fabiano Bini, Nicolò Lauciello, et al.
BioMedInformatics (2024) Vol. 4, Iss. 4, pp. 2309-2320
Open Access
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