Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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:

Automated liver lesion detection in 68Ga DOTATATE PET/CT using a deep fully convolutional neural network
Jonathan Wehrend, Michael Silosky, Fuyong Xing, et al.
EJNMMI Research (2021) Vol. 11, Iss. 1
Open Access | Times Cited: 26

Showing 1-25 of 26 citing articles:

The Role of AI in the Evaluation of Neuroendocrine Tumors: Current State of the Art
Felipe Lopez-Ramirez, Mohammad Yasrab, Florent Tixier, et al.
Seminars in Nuclear Medicine (2025)
Closed Access | Times Cited: 2
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: 15
Full-Body Tumor Response Heterogeneity of Metastatic Neuroendocrine Tumor Patients Undergoing Peptide Receptor Radiopharmaceutical Therapy
Victor Santoro-Fernandes, Brayden Schott, Amy J. Weisman, et al.
Journal of Nuclear Medicine (2025), pp. jnumed.124.267809-jnumed.124.267809
Closed Access | Times Cited: 1
An update on the diagnosis of gastroenteropancreatic neuroendocrine neoplasms
Jiayun M. Fang, Jay Li, Jiaqi Shi
World Journal of Gastroenterology (2022) Vol. 28, Iss. 10, pp. 1009-1023
Open Access | Times Cited: 32
Clinical application of AI-based PET images in oncological patients
Jiaona Dai, Hui Wang, Yuchao Xu, et al.
Seminars in Cancer Biology (2023) Vol. 91, pp. 124-142
Closed Access | Times Cited: 19
Application of Artificial Intelligence in Oncologic Molecular PET-Imaging: A Narrative Review on Beyond [18F]F-FDG Tracers - Part I. PSMA, Choline, and DOTA Radiotracers
Seyed Ali Mirshahvalad, Roya Eisazadeh, Malihe Shahbazi-Akbari, et al.
Seminars in Nuclear Medicine (2023) Vol. 54, Iss. 1, pp. 171-180
Open Access | Times Cited: 15
Models using comprehensive, lesion-level, longitudinal [68Ga]Ga-DOTA-TATE PET-derived features lead to superior outcome prediction in neuroendocrine tumor patients treated with [177Lu]Lu-DOTA-TATE
Victor Santoro-Fernandes, Brayden Schott, Alison Deatsch, et al.
European Journal of Nuclear Medicine and Molecular Imaging (2024) Vol. 51, Iss. 11, pp. 3428-3439
Closed Access | Times Cited: 5
Artificial Intelligence in Diagnostic Medical Image Processing for Advanced Healthcare Applications
Amlan Jyoti Kalita, Abhijit Boruah, Tapan Kumar Das, et al.
Biological and medical physics series (2024), pp. 1-61
Closed Access | Times Cited: 4
An automated pheochromocytoma and paraganglioma lesion segmentation AI-model at whole-body 68Ga- DOTATATE PET/CT
Fahmida Haque, Jorge A. Carrasquillo, Evrim Türkbey, et al.
EJNMMI Research (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 3
Artificial Intelligence and Machine Learning in the Diagnosis and Management of Gastroenteropancreatic Neuroendocrine Neoplasms—A Scoping Review
Athanasios Pantelis, Panagiota A. Panagopoulou, Dimitris P. Lapatsanis
Diagnostics (2022) Vol. 12, Iss. 4, pp. 874-874
Open Access | Times Cited: 12
A hard segmentation network guided by soft segmentation for tumor segmentation on PET/CT images
Guoyu Tong, Huiyan Jiang
Biomedical Signal Processing and Control (2023) Vol. 85, pp. 104918-104918
Closed Access | Times Cited: 6
Location-Aware Encoding for Lesion Detection in $^{68}$Ga-DOTATATE Positron Emission Tomography Images
Fuyong Xing, Michael Silosky, Debashis Ghosh, et al.
IEEE Transactions on Biomedical Engineering (2023) Vol. 71, Iss. 1, pp. 247-257
Closed Access | Times Cited: 5
Applications of Artificial Intelligence and Radiomics in Molecular Hybrid Imaging and Theragnostics for Neuro-Endocrine Neoplasms (NENs)
Michele Balma, Riccardo Laudicella, E. Gallio, et al.
Life (2023) Vol. 13, Iss. 8, pp. 1647-1647
Open Access | Times Cited: 4
Artificial Intelligence in Oncological Hybrid Imaging
Benedikt Feuerecker, Maurice M. Heimer, Thomas Geyer, et al.
RöFo - Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren (2022) Vol. 195, Iss. 02, pp. 105-114
Open Access | Times Cited: 6
AI-based quantification of whole-body tumour burden on somatostatin receptor PET/CT
Anni Gålne, Olof Enqvist, Anna Sundlöv, et al.
European Journal of Hybrid Imaging (2023) Vol. 7, Iss. 1
Open Access | Times Cited: 3
Current status and future of targeted peptide receptor radionuclide positron emission tomography imaging and therapy of gastroenteropancreatic-neuroendocrine tumors
Neil Grey, Michael Silosky, Christopher H. Lieu, et al.
World Journal of Gastroenterology (2022) Vol. 28, Iss. 17, pp. 1768-1780
Open Access | Times Cited: 5
Whole-body tumor burden in PET/CT expert review
Dihego Ferreira dos Santos, Maria Emília Seren Takahashi, Mariana Camacho, et al.
Clinical and Translational Imaging (2022) Vol. 11, Iss. 1, pp. 5-22
Closed Access | Times Cited: 4
Modeling contrast-to-noise ratio from list mode reconstructions of 68Ga DOTATATE PET/CT: predicting detectability of hepatic metastases in shorter acquisition PET reconstructions.
Michael Silosky, Fuyong Xing, John Wehrend, et al.
PubMed (2023) Vol. 13, Iss. 1, pp. 33-42
Closed Access | Times Cited: 2
Learning Without Real Data Annotations to Detect Hepatic Lesions in PET Images
Xinyi Yang, Bennett B. Chin, Michael Silosky, et al.
IEEE Transactions on Biomedical Engineering (2023) Vol. 71, Iss. 2, pp. 679-688
Closed Access | Times Cited: 2
Artificial Intelligence and Radiomics Applications in Neuro-endocrine Neoplasms (NENs): New Tools for Molecular Hybrid Imaging and Theragnostics Approaches
Michele Balma, Riccardo Laudicella, E. Gallio, et al.
(2023)
Open Access | Times Cited: 1
Radiology Decision Support System for Selecting Appropriate CT Imaging Titles Using Machine Learning Techniques Based on Electronic Medical Records
Peyman Shokrollahi, Juan Manuel Zambrano Chaves, Jonathan P. H. Lam, et al.
IEEE Access (2023) Vol. 11, pp. 99222-99236
Open Access | Times Cited: 1
Learning with Synthesized Data for Generalizable Lesion Detection in Real PET Images
Xinyi Yang, Bennett B. Chin, Michael Silosky, et al.
Lecture notes in computer science (2023), pp. 116-126
Closed Access | Times Cited: 1
Improving Generalizability of PET DL Algorithms: List-Mode Reconstructions Improve DOTATATE PET Hepatic Lesion Detection Performance
Xinyi Yang, Michael Silosky, Jonathan Wehrend, et al.
Bioengineering (2024) Vol. 11, Iss. 3, pp. 226-226
Open Access
Künstliche Intelligenz in der onkologischen Hybridbildgebung
Benedikt Feuerecker, Maurice M. Heimer, Thomas Geyer, et al.
Angewandte Nuklearmedizin (2024) Vol. 47, Iss. 04, pp. 246-256
Closed Access
Artificial Intelligence in Oncological Hybrid Imaging
Benedikt Feuerecker, Maurice M. Heimer, Thomas Geyer, et al.
Nuklearmedizin - NuclearMedicine (2023) Vol. 62, Iss. 05, pp. 296-305
Closed Access
Page 1 - Next Page

Scroll to top