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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:

Inter-observer and segmentation method variability of textural analysis in pre-therapeutic FDG PET/CT in head and neck cancer
Catherine Guezennec, David Bourhis, Fanny Orlhac, et al.
PLoS ONE (2019) Vol. 14, Iss. 3, pp. e0214299-e0214299
Open Access | Times Cited: 33

Showing 1-25 of 33 citing articles:

Radiomics in PET Imaging
Fanny Orlhac, Christophe Nioche, Ivan S. Klyuzhin, et al.
PET Clinics (2021) Vol. 16, Iss. 4, pp. 597-612
Open Access | Times Cited: 58
Radiomics in prostate cancer imaging for a personalized treatment approach - current aspects of methodology and a systematic review on validated studies
Simon K. B. Spohn, A. Bettermann, Fabian Bamberg, et al.
Theranostics (2021) Vol. 11, Iss. 16, pp. 8027-8042
Open Access | Times Cited: 56
Decentralized Distributed Multi-institutional PET Image Segmentation Using a Federated Deep Learning Framework
Isaac Shiri, Alireza Vafaei Sadr, Mehdi Amini, et al.
Clinical Nuclear Medicine (2022) Vol. 47, Iss. 7, pp. 606-617
Open Access | Times Cited: 40
Radiomics and Artificial Intelligence in Radiotheranostics: A Review of Applications for Radioligands Targeting Somatostatin Receptors and Prostate-Specific Membrane Antigens
Elmira Yazdani, Parham Geramifar, Najme Karamzade-Ziarati, et al.
Diagnostics (2024) Vol. 14, Iss. 2, pp. 181-181
Open Access | Times Cited: 14
Radiomics and Digital Image Texture Analysis in Oncology (Review)
Andrey Litvin, Dmitriy Burkin, A.A. Kropinov, et al.
Sovremennye tehnologii v medicine (2021) Vol. 13, Iss. 2, pp. 97-97
Open Access | Times Cited: 50
A Systematic Review of PET Textural Analysis and Radiomics in Cancer
Manuel Piñeiro-Fiel, Alexis Moscoso, Virginia Pubul, et al.
Diagnostics (2021) Vol. 11, Iss. 2, pp. 380-380
Open Access | Times Cited: 47
Current Role of Delta Radiomics in Head and Neck Oncology
David Marcu, Cristian Grava, Loredana G. Marcu
International Journal of Molecular Sciences (2023) Vol. 24, Iss. 3, pp. 2214-2214
Open Access | Times Cited: 15
Artificial intelligence for tumor [18F]FDG-PET imaging: Advancement and future trends—part I
Alireza Safarian, Seyed Ali Mirshahvalad, Abolfazl Farbod, et al.
Seminars in Nuclear Medicine (2025)
Open Access
Toward High-Throughput Artificial Intelligence-Based Segmentation in Oncological PET Imaging
Fereshteh Yousefirizi, Abhinav K. Jha, Julia Brosch-Lenz, et al.
PET Clinics (2021) Vol. 16, Iss. 4, pp. 577-596
Open Access | Times Cited: 31
Impact of tumour region of interest delineation method for mid-treatment FDG-PET response prediction in head and neck squamous cell carcinoma undergoing radiotherapy
Yuvnik Trada, Peter Lin, Mark Lee, et al.
Quantitative Imaging in Medicine and Surgery (2023) Vol. 13, Iss. 5, pp. 2822-2836
Open Access | Times Cited: 9
Voxel-based identification of local recurrence sub-regions from pre-treatment PET/CT for locally advanced head and neck cancers
Jérémy Beaumont, Oscar Acosta, Anne Devillers, et al.
EJNMMI Research (2019) Vol. 9, Iss. 1
Open Access | Times Cited: 26
Convolutional neural networks for head and neck tumor segmentation on 7-channel multiparametric MRI: a leave-one-out analysis
Lars Bielak, Nicole Wiedenmann, Arnie Berlin, et al.
Radiation Oncology (2020) Vol. 15, Iss. 1
Open Access | Times Cited: 24
Textural and Conventional Pretherapeutic [18F]FDG PET/CT Parameters for Survival Outcome Prediction in Stage III and IV Oropharyngeal Cancer Patients
David Palomino-Fernández, Eva Milara, Álvaro Galiana, et al.
Applied Sciences (2024) Vol. 14, Iss. 4, pp. 1454-1454
Open Access | Times Cited: 2
Revolutionizing breast cancer Ki-67 diagnosis: ultrasound radiomics and fully connected neural networks (FCNN) combination method
Yanfeng Li, Wengxing Long, Hongda Zhou, et al.
Breast Cancer Research and Treatment (2024) Vol. 207, Iss. 2, pp. 453-468
Closed Access | Times Cited: 2
Review on radiomic analysis in 18F-fluorodeoxyglucose positron emission tomography for prediction of melanoma outcomes
Karim Amrane, Coline Le Meur, Philippe Thuillier, et al.
Cancer Imaging (2024) Vol. 24, Iss. 1
Open Access | Times Cited: 2
Prognostic value of pre-therapeutic FDG-PET radiomic analysis in gastro-esophageal junction cancer
Karim Amrane, Philippe Thuillier, David Bourhis, et al.
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 6
Diagnostic Value of Conventional PET Parameters and Radiomic Features Extracted from 18F-FDG-PET/CT for Histologic Subtype Classification and Characterization of Lung Neuroendocrine Neoplasms
Philippe Thuillier, Virginia Liberini, Osvaldo Rampado, et al.
Biomedicines (2021) Vol. 9, Iss. 3, pp. 281-281
Open Access | Times Cited: 15
Development and validation of a radiomic model for the diagnosis of dopaminergic denervation on [18F]FDOPA PET/CT
Victor Comte, Hugo Schmutz, David Chardin, et al.
European Journal of Nuclear Medicine and Molecular Imaging (2022) Vol. 49, Iss. 11, pp. 3787-3796
Open Access | Times Cited: 10
Clinical Significance of Peritumoral Adipose Tissue PET/CT Imaging Features for Predicting Axillary Lymph Node Metastasis in Patients with Breast Cancer
Jeong Won Lee, Sung Yong Kim, Sun Wook Han, et al.
Journal of Personalized Medicine (2021) Vol. 11, Iss. 10, pp. 1029-1029
Open Access | Times Cited: 13
Hotspot on 18F-FET PET/CT to Predict Aggressive Tumor Areas for Radiotherapy Dose Escalation Guiding in High-Grade Glioma
Bastien Allard, Brieg Dissaux, David Bourhis, et al.
Cancers (2022) Vol. 15, Iss. 1, pp. 98-98
Open Access | Times Cited: 8
Deciphering Tumor Response: The Role of Fluoro-18-d-Glucose Uptake in Evaluating Targeted Therapies with Tyrosine Kinase Inhibitors
Kalevi Kairemo, Mohamed A. Gouda, Hubert H. Chuang, et al.
Journal of Clinical Medicine (2024) Vol. 13, Iss. 11, pp. 3269-3269
Open Access | Times Cited: 1
Development of a nomogram based on radiomics and semantic features for predicting chromosome 7 gain/chromosome 10 loss in IDH wild-type histologically low-grade gliomas
Xin Kong, Yu M, Fengjun Xi, et al.
Frontiers in Oncology (2023) Vol. 13
Open Access | Times Cited: 2
Optimizing SUV Analysis: A Multicenter Study on Preclinical FDG-PET/CT Highlights the Impact of Standardization
Claudia Kuntner, Carlos Alcaide, Dimitris Anestis, et al.
Molecular Imaging and Biology (2024) Vol. 26, Iss. 4, pp. 668-679
Open Access
18F-Fluorodeoxyglucose Positron Emission Tomography-Based Risk Score Model for Prediction of Five-Year Survival Outcome after Curative Resection of Non-Small-Cell Lung Cancer
Chae Hong Lim, Sang‐Won Um, Hong Kwan Kim, et al.
Cancers (2024) Vol. 16, Iss. 14, pp. 2525-2525
Open Access
Peritumoral Adipose Tissue Features Derived from [18F]fluoro-2-deoxy-2-d-glucose Positron Emission Tomography/Computed Tomography as Predictors for Response to Neoadjuvant Chemotherapy in Breast Cancer Patients
Jeong Won Lee, Yong Kyun Won, Hyein Ahn, et al.
Journal of Personalized Medicine (2024) Vol. 14, Iss. 9, pp. 952-952
Open Access
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