John C. Ford

2.2k total citations
82 papers, 1.7k citations indexed

About

John C. Ford is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Radiation. According to data from OpenAlex, John C. Ford has authored 82 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 52 papers in Radiology, Nuclear Medicine and Imaging, 25 papers in Pulmonary and Respiratory Medicine and 20 papers in Radiation. Recurrent topics in John C. Ford's work include Radiomics and Machine Learning in Medical Imaging (28 papers), Advanced Radiotherapy Techniques (20 papers) and MRI in cancer diagnosis (18 papers). John C. Ford is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (28 papers), Advanced Radiotherapy Techniques (20 papers) and MRI in cancer diagnosis (18 papers). John C. Ford collaborates with scholars based in United States, Canada and China. John C. Ford's co-authors include David Locker, Nesrin Dogan, Radka Stoyanova, Fei Yang, David B. Hackney, James L. Leake, Alan Pollack, Eric A. Mellon, Christopher M. Hand and Peter M. Joseph and has published in prestigious journals such as Journal of the American Chemical Society, Analytical Chemistry and Cancer Research.

In The Last Decade

John C. Ford

77 papers receiving 1.6k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
John C. Ford United States 24 999 350 292 179 176 82 1.7k
Neil Woodhouse United Kingdom 27 831 0.8× 461 1.3× 94 0.3× 654 3.7× 145 0.8× 49 1.9k
Shohei Tanaka Japan 19 198 0.2× 159 0.5× 91 0.3× 19 0.1× 57 0.3× 88 1.2k
Philippe Monnier Switzerland 40 381 0.4× 3.1k 8.9× 1.1k 3.8× 29 0.2× 21 0.1× 179 4.5k
Hualin Zhang United States 21 584 0.6× 567 1.6× 157 0.5× 67 0.4× 704 4.0× 78 1.3k
Peter Lukáš Austria 29 1.1k 1.1× 858 2.5× 789 2.7× 329 1.8× 319 1.8× 79 3.5k
Chris Nutting United Kingdom 30 570 0.6× 1.3k 3.7× 111 0.4× 6 0.0× 535 3.0× 87 3.3k
Ronald E. Goans United States 17 551 0.6× 177 0.5× 87 0.3× 40 0.2× 78 0.4× 50 1.0k
Tom Johnson United Kingdom 26 678 0.7× 581 1.7× 153 0.5× 18 0.1× 13 0.1× 180 2.9k
Robert Kim United States 21 759 0.8× 922 2.6× 61 0.2× 47 0.3× 9 0.1× 54 2.7k
George M. Segall United States 24 1.1k 1.1× 750 2.1× 165 0.6× 12 0.1× 62 0.4× 67 2.2k

Countries citing papers authored by John C. Ford

Since Specialization
Citations

This map shows the geographic impact of John C. Ford's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by John C. Ford with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John C. Ford more than expected).

Fields of papers citing papers by John C. Ford

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by John C. Ford. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by John C. Ford. The network helps show where John C. Ford may publish in the future.

Co-authorship network of co-authors of John C. Ford

This figure shows the co-authorship network connecting the top 25 collaborators of John C. Ford. A scholar is included among the top collaborators of John C. Ford based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with John C. Ford. John C. Ford is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Anderson, Penny R., Nesrin Dogan, John C. Ford, et al.. (2025). Repeatability, reproducibility, and the effects of radiotherapy on radiomic features of lowfield MR-LINAC images of the prostate. Frontiers in Oncology. 14. 1408752–1408752. 2 indexed citations
2.
Ford, John C., Matthew T. Studenski, Kyle R. Padgett, et al.. (2024). Increasing the efficiency of cone-beam CT based delta-radiomics using automated contours to predict radiotherapy-related toxicities in prostate cancer. Scientific Reports. 14(1). 9563–9563. 1 indexed citations
3.
Algohary, Ahmad, Evangelia I. Zacharaki, Sandra M. Gaston, et al.. (2023). Uncovering prostate cancer aggressiveness signal in T2‐weighted MRI through a three‐reference tissues normalization technique. NMR in Biomedicine. 37(3). e5069–e5069. 2 indexed citations
4.
Azzam, Gregory, et al.. (2023). Simulated Adaptive Radiotherapy for Shrinking Glioblastoma Resection Cavities on a Hybrid MRI–Linear Accelerator. Cancers. 15(5). 1555–1555. 13 indexed citations
5.
Wen, Jie, Jing Cai, Shuang Li, et al.. (2023). Improvement of 2D cine image quality using 3D priors and cycle generative adversarial network for low field MRI‐guided radiation therapy. Medical Physics. 51(5). 3495–3509. 3 indexed citations
6.
Spieler, Benjamin, Olmo Zavala‐Romero, Eric A. Mellon, et al.. (2022). Deep Learning for Per-Fraction Automatic Segmentation of Gross Tumor Volume (GTV) and Organs at Risk (OARs) in Adaptive Radiotherapy of Cervical Cancer. Frontiers in Oncology. 12. 854349–854349. 16 indexed citations
7.
Spieler, Benjamin, Lorraine Portelance, Eric A. Mellon, et al.. (2022). Predictive Value of Delta-Radiomics Texture Features in 0.35 Tesla Magnetic Resonance Setup Images Acquired During Stereotactic Ablative Radiotherapy of Pancreatic Cancer. Frontiers in Oncology. 12. 807725–807725. 10 indexed citations
8.
Ford, John C., Kyle R. Padgett, Matthew T. Studenski, et al.. (2021). Assessment of CT to CBCT contour mapping for radiomic feature analysis in prostate cancer. Scientific Reports. 11(1). 22737–22737. 7 indexed citations
9.
Ford, John C., et al.. (2020). The role of radiomics in prostate cancer radiotherapy. Strahlentherapie und Onkologie. 196(10). 900–912. 28 indexed citations
10.
Spieler, Benjamin, Nitesh V. Patel, John C. Ford, et al.. (2019). Automatic Segmentation of Abdominal Anatomy by Artificial Intelligence (AI) in Adaptive Radiotherapy of Pancreatic Cancer. International Journal of Radiation Oncology*Biology*Physics. 105(1). E130–E131. 4 indexed citations
11.
Spieler, Benjamin, S. Samuels, Ricardo Llorente, et al.. (2019). Advantages of Radiation Therapy Simulation with 0.35 Tesla Magnetic Resonance Imaging for Stereotactic Ablation of Spinal Metastases. Practical Radiation Oncology. 10(5). 339–344. 7 indexed citations
12.
Yang, Fei, Nesrin Dogan, Radka Stoyanova, & John C. Ford. (2018). Evaluation of radiomic texture feature error due to MRI acquisition and reconstruction: A simulation study utilizing ground truth. Physica Medica. 50. 26–36. 90 indexed citations
13.
Pollack, Alan, Sanoj Punnen, John C. Ford, et al.. (2018). Automatic Detection of Prostate Tumor Habitats using Diffusion MRI. Scientific Reports. 8(1). 16801–16801. 10 indexed citations
14.
15.
Stoyanova, Radka, Mandeep Takhar, John C. Ford, et al.. (2016). Prostate cancer radiomics and the promise of radiogenomics. Translational Cancer Research. 5(4). 432–447. 105 indexed citations
16.
Ford, John C., et al.. (1998). Dependence of apparent diffusion coefficients on axonal spacing, membrane permeability, and diffusion time in spinal cord white matter. Journal of Magnetic Resonance Imaging. 8(4). 775–782. 78 indexed citations
17.
Ford, John C. & Jaeju Ko. (1996). Comparison of methods for extracting linear solvent strength gradient parameters from gradient chromatographic data. Journal of Chromatography A. 727(1). 1–11. 13 indexed citations
18.
Locker, David & John C. Ford. (1994). Evaluation of an area‐based measure as an indicator of inequalities in oral health. Community Dentistry And Oral Epidemiology. 22(2). 80–85. 36 indexed citations
19.
Ford, John C., David B. Hackney, David C. Alsop, et al.. (1994). MRI characterization of diffusion coefficients in a rat spinal cord injury model. Magnetic Resonance in Medicine. 31(5). 488–494. 147 indexed citations
20.
Ford, John C.. (1956). The General Practitioner's Role in Alcoholism. The Linacre Quarterly. 23(4). 1. 1 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Neil Woodhouse Breakdown of academic impact, for papers by Shohei Tanaka Breakdown of academic impact, for papers by Philippe Monnier Breakdown of academic impact, for papers by Hualin Zhang Breakdown of academic impact, for papers by Peter Lukáš Breakdown of academic impact, for papers by Chris Nutting Breakdown of academic impact, for papers by Ronald E. Goans Breakdown of academic impact, for papers by Tom Johnson Breakdown of academic impact, for papers by Robert Kim Breakdown of academic impact, for papers by George M. Segall
Rankless by CCL
2026