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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:

Radiomics Features of the Spleen as Surrogates for CT-Based Lymphoma Diagnosis and Subtype Differentiation
Johanna S. Enke, Jan Hendrik Moltz, Melvin D’Anastasi, et al.
Cancers (2022) Vol. 14, Iss. 3, pp. 713-713
Open Access | Times Cited: 18

Showing 18 citing articles:

Artificial intelligence-driven radiomics study in cancer: the role of feature engineering and modeling
Yuanpeng Zhang, Xinyun Zhang, Yu‐Ting Cheng, et al.
Military Medical Research (2023) Vol. 10, Iss. 1
Open Access | Times Cited: 91
Phantom-based radiomics feature test–retest stability analysis on photon-counting detector CT
Alexander Hertel, Hishan Tharmaseelan, Lukas T. Rotkopf, et al.
European Radiology (2023) Vol. 33, Iss. 7, pp. 4905-4914
Open Access | Times Cited: 30
Comparison Study of Myocardial Radiomics Feature Properties on Energy-Integrating and Photon-Counting Detector CT
Isabelle Ayx, Hishan Tharmaseelan, Alexander Hertel, et al.
Diagnostics (2022) Vol. 12, Iss. 5, pp. 1294-1294
Open Access | Times Cited: 25
Tumor classification of gastrointestinal liver metastases using CT-based radiomics and deep learning
Hishan Tharmaseelan, Abhinay Vellala, Alexander Hertel, et al.
Cancer Imaging (2023) Vol. 23, Iss. 1
Open Access | Times Cited: 12
Combination of Whole-Body Baseline CT Radiomics and Clinical Parameters to Predict Response and Survival in a Stage-IV Melanoma Cohort Undergoing Immunotherapy
Felix Peisen, Annika Hänsch, Alessa Hering, et al.
Cancers (2022) Vol. 14, Iss. 12, pp. 2992-2992
Open Access | Times Cited: 18
Photon-counting detector CT-based virtual monoenergetic reconstructions: repeatability and reproducibility of radiomics features of an organic phantom and human myocardium
Elias V. Wolf, Lukáš Müller, U. Joseph Schoepf, et al.
European Radiology Experimental (2023) Vol. 7, Iss. 1
Open Access | Times Cited: 10
Influence of local aortic calcification on periaortic adipose tissue radiomics texture features—a primary analysis on PCCT
Hishan Tharmaseelan, Matthias F. Froelich, Dominik Nörenberg, et al.
The International Journal of Cardiovascular Imaging (2022) Vol. 38, Iss. 11, pp. 2459-2467
Open Access | Times Cited: 14
Two-Stage Deep Learning Model for Automated Segmentation and Classification of Splenomegaly
Aymen Meddeb, Tabea Kossen, Keno K. Bressem, et al.
Cancers (2022) Vol. 14, Iss. 22, pp. 5476-5476
Open Access | Times Cited: 7
Radiomics Applications in Spleen Imaging: A Systematic Review and Methodological Quality Assessment
Salvatore Claudio Fanni, Maria Febi, Roberto Francischello, et al.
Diagnostics (2023) Vol. 13, Iss. 16, pp. 2623-2623
Open Access | Times Cited: 3
The Potential and Emerging Role of Quantitative Imaging Biomarkers for Cancer Characterization
Hishan Tharmaseelan, Alexander Hertel, Shereen Rennebaum, et al.
Cancers (2022) Vol. 14, Iss. 14, pp. 3349-3349
Open Access | Times Cited: 4
Development of a new risk scoring system based on spleen involvement and the lymphocyte/monocyte ratio for follicular lymphoma patients
Chunyuan Li, Wei Zhang, Danqing Zhao, et al.
Leukemia Research (2022) Vol. 123, pp. 106980-106980
Closed Access | Times Cited: 3
Comparison of radiomics models and dual-energy material decomposition to decipher abdominal lymphoma in contrast-enhanced CT
Simon Bernatz, Ina Koch, Daniel Pinto dos Santos, et al.
International Journal of Computer Assisted Radiology and Surgery (2023) Vol. 18, Iss. 10, pp. 1829-1839
Open Access | Times Cited: 1
Optimal index for detecting splenic involvement on 18F-fluorodeoxyglucose positron emission tomography/computed tomography imaging in diffuse large B-cell lymphoma
Ryohei Kozuki, T Sugimoto, Hideaki Goto, et al.
Medicine (2024) Vol. 103, Iss. 9, pp. e37290-e37290
Open Access
Distinguishing diffuse large B-cell lymphoma from Hodgkin’s lymphoma in children using an enhanced computed tomography radiomics approach
Jiajun Si, Haoru Wang, Mingye Xie, et al.
Translational Pediatrics (2024) Vol. 13, Iss. 5, pp. 716-726
Open Access
The value of radiomics features of the spleen as surrogates for differentiating subtypes of common pediatric lymphomas
Jiajun Si, Haoru Wang, Mingye Xie, et al.
Quantitative Imaging in Medicine and Surgery (2024) Vol. 14, Iss. 8, pp. 5630-5641
Open Access
Deep learning-derived splenic radiomics, genomics, and coronary artery disease
Meghana Kamineni, Vineet K. Raghu, Buu Truong, et al.
medRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access
The prognostic value of splenic abnormalities in pretreatment 18F-FDG PET/CT in patients with complete response diffuse large B-cell lymphoma
S Wang, H. Ju, Yana Bai, et al.
Clinical Radiology (2023) Vol. 78, Iss. 5, pp. 375-380
Closed Access
Machine Learning Radiomics Signature for Differentiating Lymphoma versus Benign Splenomegaly on CT
Jih-An Cheng, Yu‐Chun Lin, Yenpo Lin, et al.
Diagnostics (2023) Vol. 13, Iss. 24, pp. 3632-3632
Open Access
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