Christopher P. Bridge

1.6k total citations · 1 hit paper
43 papers, 593 citations indexed

About

Christopher P. Bridge is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Physiology. According to data from OpenAlex, Christopher P. Bridge has authored 43 papers receiving a total of 593 indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Radiology, Nuclear Medicine and Imaging, 13 papers in Artificial Intelligence and 8 papers in Physiology. Recurrent topics in Christopher P. Bridge's work include Radiomics and Machine Learning in Medical Imaging (19 papers), AI in cancer detection (9 papers) and Nutrition and Health in Aging (8 papers). Christopher P. Bridge is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (19 papers), AI in cancer detection (9 papers) and Nutrition and Health in Aging (8 papers). Christopher P. Bridge collaborates with scholars based in United States, United Kingdom and Germany. Christopher P. Bridge's co-authors include J. Alison Noble, C. Ioannou, Katherine P. Andriole, Florian J. Fintelmann, Kirti Magudia, Michael H. Rosenthal, Jayashree Kalpathy–Cramer, Fabian M. Troschel, Camden Bay and Brian M. Wolpin and has published in prestigious journals such as Stroke, Annals of Surgery and Scientific Reports.

In The Last Decade

Christopher P. Bridge

40 papers receiving 584 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

A review of deep learning for brain tumor analysis in MRI

2025 16 citations Jayashree Kalpathy-Cramer, Elizabeth R. Gerstner et al. npj Precision Oncology profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Christopher P. Bridge United States	14	205	140	114	89	81	43	593
Alexander D. Weston United States	12	475 2.3×	126 0.9×	207 1.8×	18 0.2×	165 2.0×	25	973
Hong Kyu Kim South Korea	16	439 2.1×	39 0.3×	73 0.6×	67 0.8×	40 0.5×	44	858
Sukrit Narula United States	13	218 1.1×	56 0.4×	56 0.5×	11 0.1×	125 1.5×	19	829
Maurizio Cariati Italy	15	190 0.9×	32 0.2×	148 1.3×	51 0.6×	233 2.9×	93	833
Rolv‐Ole Lindsetmo Norway	14	103 0.5×	33 0.2×	137 1.2×	18 0.2×	332 4.1×	36	791
Kenneth Fung United Kingdom	17	460 2.2×	78 0.6×	28 0.2×	13 0.1×	118 1.5×	43	1.3k
Hiroyuki Sugimori Japan	14	356 1.7×	31 0.2×	55 0.5×	32 0.4×	151 1.9×	93	767
Linyuan Jing United States	16	288 1.4×	21 0.1×	65 0.6×	24 0.3×	121 1.5×	36	855
Ryan Zea United States	13	329 1.6×	149 1.1×	16 0.1×	9 0.1×	195 2.4×	36	791
Youngbin Shin South Korea	15	498 2.4×	512 3.7×	214 1.9×	10 0.1×	206 2.5×	30	1.3k

Countries citing papers authored by Christopher P. Bridge

Since Specialization

Citations

This map shows the geographic impact of Christopher P. Bridge'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 Christopher P. Bridge with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Christopher P. Bridge more than expected).

Fields of papers citing papers by Christopher P. Bridge

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Christopher P. Bridge. 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 Christopher P. Bridge. The network helps show where Christopher P. Bridge may publish in the future.

Co-authorship network of co-authors of Christopher P. Bridge

This figure shows the co-authorship network connecting the top 25 collaborators of Christopher P. Bridge. A scholar is included among the top collaborators of Christopher P. Bridge 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 Christopher P. Bridge. Christopher P. Bridge is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Tripathi, Satvik, Azadeh Tabari, Bernardo C. Bizzo, et al.. (2025). PRECISE framework: Enhanced radiology reporting with GPT for improved readability, reliability, and patient-centered care. European Journal of Radiology. 187. 112124–112124. 1 indexed citations

Kalpathy-Cramer, Jayashree, et al.. (2025). A review of deep learning for brain tumor analysis in MRI. npj Precision Oncology. 9(1). 2–2. 16 indexed citations breakdown →

Bontempi, Dennis, et al.. (2024). Enrichment of lung cancer computed tomography collections with AI-derived annotations. Scientific Data. 11(1). 25–25. 2 indexed citations

Bridge, Christopher P., et al.. (2024). Diffusion tensor transformation for personalizing target volumes in radiation therapy. Medical Image Analysis. 97. 103271–103271. 1 indexed citations

Chen, Yen‐Lin, et al.. (2024). Integrating muscle fiber orientation from visible human data into radiotherapy target volumes. Physics in Medicine and Biology. 69(14). 145006–145006. 1 indexed citations

Bridge, Christopher P., G Sharp, Sune Nørhøj Jespersen, et al.. (2024). Investigating the potential of diffusion tensor atlases to generate anisotropic clinical tumor volumes in glioblastoma patients. Physics and Imaging in Radiation Oncology. 33. 100688–100688.

Busch, Felix, Lisa C. Adams, Thomas Schultz, et al.. (2024). Comparing Commercial and Open-Source Large Language Models for Labeling Chest Radiograph Reports. Radiology. 313(1). e241139–e241139. 7 indexed citations

Mansur, Arian, Omar M. Omar, Khalid Ahmed, et al.. (2024). Beyond MELD Score: Association of Machine Learning-derived CT Body Composition with 90-Day Mortality Post Transjugular Intrahepatic Portosystemic Shunt Placement. CardioVascular and Interventional Radiology. 48(2). 221–230. 2 indexed citations

Hoebel, Katharina, Christopher P. Bridge, Sara Ahmed, et al.. (2023). Expert-centered Evaluation of Deep Learning Algorithms for Brain Tumor Segmentation. Radiology Artificial Intelligence. 6(1). e220231–e220231. 4 indexed citations

10.

Kim, Kyungsang, Fabíola Macruz, Dufan Wu, et al.. (2023). Point-of-care AI-assisted stepwise ultrasound pneumothorax diagnosis. Physics in Medicine and Biology. 68(20). 205013–205013. 13 indexed citations

11.

Mansur, Arian, et al.. (2023). Role of Machine Learning-Based CT Body Composition in Risk Prediction and Prognostication: Current State and Future Directions. Diagnostics. 13(5). 968–968. 17 indexed citations

12.

Bridge, Christopher P., Till D. Best, Maria Wróbel, et al.. (2022). A Fully Automated Deep Learning Pipeline for Multi–Vertebral Level Quantification and Characterization of Muscle and Adipose Tissue on Chest CT Scans. Radiology Artificial Intelligence. 4(1). e210080–e210080. 27 indexed citations

13.

Patel, Jay, Bernardo C. Bizzo, Daniel I. Glazer, et al.. (2022). Machine Learning for Adrenal Gland Segmentation and Classification of Normal and Adrenal Masses at CT. Radiology. 306(2). e220101–e220101. 23 indexed citations

14.

Bridge, Christopher P., Steven C. Pieper, Jochen K. Lennerz, et al.. (2022). Highdicom: a Python Library for Standardized Encoding of Image Annotations and Machine Learning Model Outputs in Pathology and Radiology. Journal of Digital Imaging. 35(6). 1719–1737. 9 indexed citations

15.

Magudia, Kirti, Christopher P. Bridge, Katherine P. Andriole, & Michael H. Rosenthal. (2021). The Trials and Tribulations of Assembling Large Medical Imaging Datasets for Machine Learning Applications. Journal of Digital Imaging. 34(6). 1424–1429. 10 indexed citations

16.

Laur, Olga, Michael J. Weaver, Christopher P. Bridge, et al.. (2021). Computed tomography-based body composition profile as a screening tool for geriatric frailty detection. Skeletal Radiology. 51(7). 1371–1380. 8 indexed citations

17.

Best, Till D., Eric Roeland, Nora Horick, et al.. (2021). Muscle Loss Is Associated with Overall Survival in Patients with Metastatic Colorectal Cancer Independent of Tumor Mutational Status and Weight Loss. The Oncologist. 26(6). e963–e970. 18 indexed citations

18.

Vigneault, Davis M., et al.. (2021). M-SiSSR: Regional Endocardial Function Using Multilabel Simultaneous Subdivision Surface Registration. Lecture notes in computer science. 12738. 242–252. 1 indexed citations

19.

Magudia, Kirti, Christopher P. Bridge, Camden Bay, et al.. (2020). Population-Scale CT-based Body Composition Analysis of a Large Outpatient Population Using Deep Learning to Derive Age-, Sex-, and Race-specific Reference Curves. Radiology. 298(2). 319–329. 98 indexed citations

20.

Bridge, Christopher P., C. Ioannou, & J. Alison Noble. (2016). Automated annotation and quantitative description of ultrasound videos of the fetal heart. Medical Image Analysis. 36. 147–161. 45 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.

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