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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:

Fully Automatic Calibration of Tumor-Growth Models Using a Single mpMRI Scan
Klaudius Scheufele, Shashank Subramanian, George Biros
IEEE Transactions on Medical Imaging (2020) Vol. 40, Iss. 1, pp. 193-204
Open Access | Times Cited: 24

Showing 24 citing articles:

Integrating mechanism-based modeling with biomedical imaging to build practical digital twins for clinical oncology
Chengyue Wu, Guillermo Lorenzo, David A. Hormuth, et al.
Biophysics Reviews (2022) Vol. 3, Iss. 2
Open Access | Times Cited: 67
Novel approach to classify brain tumor based on transfer learning and deep learning
Sachin Jain, Vishal Jain
International Journal of Information Technology (2023) Vol. 15, Iss. 4, pp. 2031-2038
Closed Access | Times Cited: 23
Cardiac Healthcare Digital Twins Supported by Artificial Intelligence-Based Algorithms and Extended Reality—A Systematic Review
Zofia Rudnicka, Klaudia Proniewska, Mark D. Perkins, et al.
Electronics (2024) Vol. 13, Iss. 5, pp. 866-866
Open Access | Times Cited: 15
Identifiability and model selection frameworks for models of high-grade glioma response to chemoradiation
Khushi C. Hiremath, Kenan Atakishi, Ernesto A. B. F. Lima, et al.
Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences (2025) Vol. 383, Iss. 2293
Open Access | Times Cited: 1
MRI-based digital twins to improve treatment response of breast cancer by optimizing neoadjuvant chemotherapy regimens
Chengyue Wu, Ernesto A. B. F. Lima, Casey Stowers, et al.
npj Digital Medicine (2025) Vol. 8, Iss. 1
Open Access | Times Cited: 1
Designing clinical trials for patients who are not average
Thomas E. Yankeelov, David A. Hormuth, Ernesto A. B. F. Lima, et al.
iScience (2023) Vol. 27, Iss. 1, pp. 108589-108589
Open Access | Times Cited: 16
SPBTGNS: Design of an Efficient Model for Survival Prediction in Brain Tumour Patients using Generative Adversarial Network with Neural Architectural Search Operations
Ruqsar Zaitoon, Sachi Nandan Mohanty, Deepthi Godavarthi, et al.
IEEE Access (2024) Vol. 12, pp. 140847-140869
Open Access | Times Cited: 6
Computer Vision Techniques for Growth Prediction: A Prisma-Based Systematic Literature Review
Yojiro Harie, Bishnu Prasad Gautam, Katsumi Wasaki
Applied Sciences (2023) Vol. 13, Iss. 9, pp. 5335-5335
Open Access | Times Cited: 10
Contrast Enhancement of Multiple Tissues in MR Brain Images With Reversibility
Hao‐Tian Wu, Kaihan Zheng, Qi Huang, et al.
IEEE Signal Processing Letters (2021) Vol. 28, pp. 160-164
Open Access | Times Cited: 20
Visually communicating pathological changes: A case study on the effectiveness of phong versus outline shading
Sarah Mittenentzwei, Sophie Mlitzke, Darija Grisanova, et al.
Computers & Graphics (2024) Vol. 123, pp. 104023-104023
Open Access | Times Cited: 2
Ensemble Inversion for Brain Tumor Growth Models With Mass Effect
Shashank Subramanian, Ali Ghafouri, Klaudius Scheufele, et al.
IEEE Transactions on Medical Imaging (2022) Vol. 42, Iss. 4, pp. 982-995
Open Access | Times Cited: 11
Quantitative In Vivo Imaging to Enable Tumour Forecasting and Treatment Optimization
Guillermo Lorenzo, David A. Hormuth, Angela M. Jarrett, et al.
Emergence, complexity and computation (2022), pp. 55-97
Closed Access | Times Cited: 10
A global sensitivity analysis of a mechanistic model of neoadjuvant chemotherapy for triple negative breast cancer constrained by in vitro and in vivo imaging data
Guillermo Lorenzo, Angela M. Jarrett, Christian T. Meyer, et al.
Engineering With Computers (2023) Vol. 40, Iss. 3, pp. 1469-1499
Open Access | Times Cited: 4
Deep Learning for Reaction-Diffusion Glioma Growth Modeling: Towards a Fully Personalized Model?
Corentin Martens, Antonin Rovaï, Daniele Bonatto, et al.
Cancers (2022) Vol. 14, Iss. 10, pp. 2530-2530
Open Access | Times Cited: 7
Health Digital Twins Supported by Artificial Intelligence-based Algorithms and Extended Reality in Cardiology
Zofia Rudnicka, Klaudia Proniewska, Mark D. Perkins, et al.
arXiv (Cornell University) (2024)
Open Access | Times Cited: 1
Personalized predictions of Glioblastoma infiltration: Mathematical models, Physics-Informed Neural Networks and multimodal scans
Zirui Zhang, Ivan Ezhov, Michał Balcerak, et al.
Medical Image Analysis (2024) Vol. 101, pp. 103423-103423
Open Access | Times Cited: 1
Modeling of glioma growth using modified reaction-diffusion equation on brain MR images
Yanying Zhang, Peter Liu, Wenguo Hou
Computer Methods and Programs in Biomedicine (2022) Vol. 227, pp. 107233-107233
Closed Access | Times Cited: 5
CLAIRE: Constrained Large Deformation Diffeomorphic Image Registration on Parallel Computing Architectures
Malte Brunn, Naveen Himthani, George Biros, et al.
The Journal of Open Source Software (2021) Vol. 6, Iss. 61, pp. 3038-3038
Open Access | Times Cited: 5
Quantitative in vivo imaging to enable tumor forecasting and treatment optimization
Guillermo Lorenzo, David A. Hormuth, Angela M. Jarrett, et al.
arXiv (Cornell University) (2021)
Open Access | Times Cited: 4
Accelerating Parameter Inference in Diffusion-Reaction Models of Glioblastoma Using Physics-Informed Neural Networks
Andy Zhu
SIAM Undergraduate Research Online (2022) Vol. 15
Open Access | Times Cited: 3
A 3D Inverse Solver for a Multi-species PDE Model of Glioblastoma Growth
Ali Ghafouri, George Biros
Lecture notes in computer science (2023), pp. 51-60
Closed Access | Times Cited: 1
Modeling free tumor growth: Discrete, continuum, and hybrid approaches to interpreting cancer development
Dashmi Singh, Dana Paquin
Mathematical Biosciences & Engineering (2024) Vol. 21, Iss. 7, pp. 6659-6693
Open Access
Single-Scan mpMRI Calibration of Multi-species Brain Tumor Dynamics with Mass Effect
Ali Ghafouri, George Biros
Lecture notes in computer science (2024), pp. 187-196
Closed Access
Learning Tumor-Induced Deformations to Improve Tumor-Bearing Brain MR Segmentation
Jia Meng, Matthew Kyan
Lecture notes in computer science (2022), pp. 245-255
Closed Access
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