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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:

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

Showing 16 citing articles:

Radiomics for clinical decision support in radiation oncology
Luca Russo, Diepriye Charles-Davies, Silvia Bottazzi, et al.
Clinical Oncology (2024) Vol. 36, Iss. 8, pp. e269-e281
Open Access | Times Cited: 6
Systematic review and meta-analysis of deep learning applications in computed tomography lung cancer segmentation
Tingwei Wang, Jia‐Sheng Hong, Jing-Wen Huang, et al.
Radiotherapy and Oncology (2024) Vol. 197, pp. 110344-110344
Closed Access | Times Cited: 6
Implementing a deep learning model for automatic tongue tumour segmentation in ex-vivo 3-dimensional ultrasound volumes
N. M. Bekedam, Luuk H.W. Idzerda, Maarten J. A. van Alphen, et al.
British Journal of Oral and Maxillofacial Surgery (2024) Vol. 62, Iss. 3, pp. 284-289
Open Access | Times Cited: 4
Segmentation method of magnetic resonance imaging brain tumor images based on improved UNet network
Yang Yang, Peng Wang, Zhenyu Yang, et al.
Translational Cancer Research (2024) Vol. 13, Iss. 3, pp. 1567-1583
Open Access | Times Cited: 4
Preoperative prediction of the Lauren classification in gastric cancer using automated nnU-Net and radiomics: a multicenter study
Bo Cao, Jun Hu, Haige Li, et al.
Insights into Imaging (2025) Vol. 16, Iss. 1
Open Access
Automated detection of small hepatocellular carcinoma in cirrhotic livers: applying deep learning to Gd-EOB-DTPA-enhanced MRI
Junqiang Lei, Yongsheng Xu, Yongwen Zhu, et al.
Abdominal Radiology (2025)
Closed Access
Optimizing CBCT Analysis of the Adenoid Region: A Deep Learning Approach
Ameena Nihal, Meruja Selvamanikkam, Swarna Yerebairapura Math, et al.
(2025), pp. 100013-100013
Open Access
Atherosclerotic carotid artery disease Radiomics: A systematic review with meta-analysis and radiomic quality score assessment
Sebastiano Vacca, Roberta Scicolone, Ajay Gupta, et al.
European Journal of Radiology (2024) Vol. 177, pp. 111547-111547
Closed Access | Times Cited: 3
PET radiomics in lung cancer: advances and translational challenges
Yongbai Zhang, Wenpeng Huang, Hao Jiao, et al.
EJNMMI Physics (2024) Vol. 11, Iss. 1
Open Access | Times Cited: 3
Association between Contrast-Enhanced Computed Tomography Radiomic Features, Genomic Alterations and Prognosis in Advanced Lung Adenocarcinoma Patients
Lisa Rinaldi, Elena Guerini‐Rocco, Gianluca Spitaleri, et al.
Cancers (2023) Vol. 15, Iss. 18, pp. 4553-4553
Open Access | Times Cited: 4
Autocontouring of primary lung lesions and nodal disease for radiotherapy based only on computed tomography images
Stephen Skett, Tina Patel, Didier Duprez, et al.
Physics and Imaging in Radiation Oncology (2024) Vol. 31, pp. 100637-100637
Open Access | Times Cited: 1
Combining Handcrafted Features and Deep Learning for Automatic Classification of Lung Cancer on CT Scans
Pallavi S. Deshpande, Mohammed Wasim Bhatt, Santaji Krishna Shinde, et al.
Journal of Artificial Intelligence and Technology (2023)
Open Access | Times Cited: 2
Clinical Acceptability of Ct-Only Automated Contouring of Treatment Targets for Palliative Radiotherapy of Lung Cancer
Stephen Skett, Tina Patel, Didier Duprez, et al.
(2024)
Closed Access
Training and assessing convolutional neural network performance in automatic vascular segmentation using Ga-68 DOTATATE PET/CT
Rodney Parry, K. Wright, J. Bellinge, et al.
The International Journal of Cardiovascular Imaging (2024) Vol. 40, Iss. 9, pp. 1847-1861
Open Access
Multitask connected U-Net: automatic lung cancer segmentation from CT images using PET knowledge guidance
Lu Zhou, Chaoyong Wu, Yiheng Chen, et al.
Frontiers in Artificial Intelligence (2024) Vol. 7
Open Access
Self-Configuring Capsule Networks for Brain Image Segmentation
Arman Avesta, Sajid Hossain, Mariam Aboian, et al.
medRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access
Automatic liver segmentation and assessment of liver fibrosis using deep learning with MR T1-weighted images in rats
Wenjing Zhang, Nan Zhao, Yuanxiang Gao, et al.
Magnetic Resonance Imaging (2023) Vol. 107, pp. 1-7
Closed Access
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