Nathan Cross

569 total citations
34 papers, 288 citations indexed

About

Nathan Cross is a scholar working on Radiology, Nuclear Medicine and Imaging, Biomedical Engineering and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Nathan Cross has authored 34 papers receiving a total of 288 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Radiology, Nuclear Medicine and Imaging, 17 papers in Biomedical Engineering and 8 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Nathan Cross's work include Medical Imaging and Analysis (7 papers), Radiomics and Machine Learning in Medical Imaging (5 papers) and Advanced MRI Techniques and Applications (5 papers). Nathan Cross is often cited by papers focused on Medical Imaging and Analysis (7 papers), Radiomics and Machine Learning in Medical Imaging (5 papers) and Advanced MRI Techniques and Applications (5 papers). Nathan Cross collaborates with scholars based in United States, Finland and Ireland. Nathan Cross's co-authors include Daniel S. Hippe, Mahmud Mossa‐Basha, Elwin de Weerdt, Justin E. Vranic, Michael N. Hoff, Kalpana M. Kanal, Christopher S. Hall, Axel Saalbach, Jalal B. Andre and Jeffrey G. Jarvik and has published in prestigious journals such as Journal of Controlled Release, Magnetic Resonance in Medicine and Frontiers in Immunology.

In The Last Decade

Nathan Cross

30 papers receiving 285 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Nathan Cross United States 8 184 93 39 28 27 34 288
Pin Lin Kei Singapore 9 110 0.6× 125 1.3× 78 2.0× 57 2.0× 18 0.7× 18 332
Brendan Eck United States 12 272 1.5× 164 1.8× 66 1.7× 26 0.9× 20 0.7× 46 433
Christian P. Mol Netherlands 12 288 1.6× 119 1.3× 39 1.0× 102 3.6× 18 0.7× 18 447
Chankue Park South Korea 9 197 1.1× 162 1.7× 63 1.6× 16 0.6× 8 0.3× 32 269
Jannis Bodden Germany 10 163 0.9× 129 1.4× 57 1.5× 48 1.7× 12 0.4× 35 339
Eric K. Gibbons United States 5 281 1.5× 90 1.0× 29 0.7× 15 0.5× 11 0.4× 7 393
Ibolya Csécs United States 16 164 0.9× 66 0.7× 34 0.9× 55 2.0× 8 0.3× 31 422
Yihang Zhou China 9 292 1.6× 92 1.0× 20 0.5× 76 2.7× 12 0.4× 48 347
Bragi Sveinsson United States 10 162 0.9× 72 0.8× 78 2.0× 7 0.3× 19 0.7× 18 290

Countries citing papers authored by Nathan Cross

Since Specialization
Citations

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

Fields of papers citing papers by Nathan Cross

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Nathan Cross. 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 Nathan Cross. The network helps show where Nathan Cross may publish in the future.

Co-authorship network of co-authors of Nathan Cross

This figure shows the co-authorship network connecting the top 25 collaborators of Nathan Cross. A scholar is included among the top collaborators of Nathan Cross 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 Nathan Cross. Nathan Cross 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.
Leu, Justin, Ted Gooley, Nathan Cross, et al.. (2025). Evaluating risk factors for skeletal-related events among bone metastases from solid tumors. Radiotherapy and Oncology. 211. 111048–111048.
2.
Brunnquell, Christina L., Michael N. Hoff, Jalal B. Andre, et al.. (2025). A Comparison of Radiography, X-Ray Tomosynthesis, and CT for Intraorbital Metallic Foreign Body Screening. Journal of the American College of Radiology. 22(3). 386–394. 1 indexed citations
3.
Jennewein, Madeleine F., Eric Lo, Nathan Cross, et al.. (2025). An intranasally- and intramuscularly-deliverable nanostructured lipid carrier-replicon RNA vaccine drives protective systemic and mucosal immunity. Journal of Controlled Release. 385. 114054–114054.
4.
Kasal, Darshan N., Madeleine F. Jennewein, Nathan Cross, et al.. (2025). A bivalent self-amplifying RNA vaccine against yellow fever and Zika viruses. Frontiers in Immunology. 16. 1569454–1569454. 3 indexed citations
5.
King, Wilson, Zachary Miller, Patrick J. Heagerty, et al.. (2025). High-Performance Prompting for LLM Extraction of Compression Fracture Findings from Radiology Reports. Journal of Imaging Informatics in Medicine. 39(1). 973–988.
6.
Lowry, Kathryn P., et al.. (2024). Establishing a Validation Infrastructure for Imaging-Based Artificial Intelligence Algorithms Before Clinical Implementation. Journal of the American College of Radiology. 21(10). 1569–1574. 7 indexed citations
7.
Cross, Nathan, Gang Luo, Nancy E. Lane, et al.. (2024). Subject-level spinal osteoporotic fracture prediction combining deep learning vertebral outputs and limited demographic data. Archives of Osteoporosis. 19(1). 87–87.
8.
Bresnahan, Brian W., et al.. (2024). Cost-Effectiveness of Artificial Intelligence–Based Opportunistic Compression Fracture Screening of Existing Radiographs. Journal of the American College of Radiology. 21(9). 1489–1496. 7 indexed citations
9.
10.
Luo, Gang, Nancy E. Lane, Li‐Yung Lui, et al.. (2022). Deep Learning Classification of Spinal Osteoporotic Compression Fractures on Radiographs using an Adaptation of the Genant Semiquantitative Criteria. Academic Radiology. 29(12). 1819–1832. 32 indexed citations
11.
O’Reilly, Michael K., et al.. (2022). m2ABQ—a proposed refinement of the modified algorithm-based qualitative classification of osteoporotic vertebral fractures. Osteoporosis International. 34(1). 137–145. 1 indexed citations
12.
Sarıkaya, Başar, et al.. (2021). The role of imaging in the management of non-traumatic subarachnoid hemorrhage: a practical review. Emergency Radiology. 28(4). 797–808. 3 indexed citations
13.
Sommer, Karsten, Axel Saalbach, Tom Brosch, et al.. (2020). Correction of Motion Artifacts Using a Multiscale Fully Convolutional Neural Network. American Journal of Neuroradiology. 41(3). 416–423. 32 indexed citations
14.
O’Reilly, Michael K., Michael N. Hoff, Seth D. Friedman, James F. Jones, & Nathan Cross. (2020). Simulating Tissues with 3D-Printed and Castable Materials. Journal of Digital Imaging. 33(5). 1280–1291. 17 indexed citations
15.
Cross, Nathan, et al.. (2019). The voice of the radiologist: Enabling patients to speak directly to radiologists. Clinical Imaging. 61. 84–89. 6 indexed citations
16.
Cross, Nathan, Michael N. Hoff, & Kalpana M. Kanal. (2018). Avoiding MRI-Related Accidents: A Practical Approach to Implementing MR Safety. Journal of the American College of Radiology. 15(12). 1738–1744. 25 indexed citations
17.
Cross, Nathan, et al.. (2018). Practical CT Dose Monitoring: Current Tools and the Clinical Relevance. Seminars in Roentgenology. 53(2). 115–123. 3 indexed citations
18.
Vranic, Justin E., et al.. (2018). Compressed Sensing–Sensitivity Encoding (CS-SENSE) Accelerated Brain Imaging: Reduced Scan Time without Reduced Image Quality. American Journal of Neuroradiology. 40(1). 92–98. 86 indexed citations
19.
Chen, Po‐Hao & Nathan Cross. (2018). IoT in Radiology: Using Raspberry Pi to Automatically Log Telephone Calls in the Reading Room. Journal of Digital Imaging. 31(3). 371–378. 8 indexed citations
20.

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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