Jonathan Stoeckel

585 citations
11 papers · 341 · h-index 6

Impact in

Papers in

Jonathan Stoeckel

11 papers receiving 324 citations

Peers

Jonathan Stoeckel
Comparison fields: 5 of 55
  • Neurology 83
  • Computer Vision and Pattern Recognition 108
  • Health Information Management 21
  • Radiology, Nuclear Medicine and Imaging 76
  • Computational Mathematics 2
Replace Yechong Huang with:
Yechong Huang China
Nagaraj Yamanakkanavar South Korea
Yulia Dodonova Russia
Wenyong Zhu China
Jiahang Xu China
Sergey Korolev Russia
Ammarah Farooq United Kingdom
Waleed M. Bahgat Egypt
Xinyan Zhao China
Akshay Pai Denmark
Jonathan Stoeckel relative to Yechong Huang China Yechong Huang's profile →
Citations per field
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Yechong Huang · 1×
Citations per year

Countries citing papers authored by Jonathan Stoeckel

Since Specialization
Citations

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

Fields of papers citing papers by Jonathan Stoeckel

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Jonathan Stoeckel, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jonathan Stoeckel Line = papers co-authored together Jonathan Stoeckel links everyone, so they are left out of the graph.

All Works

11 of 11 papers shown
#Work
1 2006125
2 2006108
3 200773
4 20028
5 20048
6 20015
7
Smoothness and degrees of freedom restrictions when using SPM 99
20014
8 20053
9 20063
10 20023
11 20081

About Jonathan Stoeckel

Jonathan Stoeckel is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine, Computer Vision and Pattern Recognition, Neurology and Molecular Biology, having authored 11 papers that have together received 341 indexed citations. Recurring topics across this work include Lung Cancer Diagnosis and Treatment (4 papers), Radiomics and Machine Learning in Medical Imaging (3 papers), Medical Image Segmentation Techniques (2 papers), Radiology practices and education (2 papers), Image Retrieval and Classification Techniques (2 papers), Neurological Disease Mechanisms and Treatments (2 papers), Digital Radiography and Breast Imaging (2 papers) and Radioactive Decay and Measurement Techniques (1 paper). The work is most often cited by research in Neurology (83 citations), Computer Vision and Pattern Recognition (108 citations), Health Information Management (21 citations), Radiology, Nuclear Medicine and Imaging (76 citations) and Computational Mathematics (2 citations). Jonathan Stoeckel has collaborated with scholars based in United States, Germany and France. Frequent co-authors include Glenn Fung, Eva Maria Fallenberg, Kai Uwe Juergens, Dag Wormanns, Florian Beyer, Walter Heindel, Nicholas Ayache, Grégoire Malandain, Jean‐Baptiste Poline and Jacques Darcourt. Their work appears in journals such as European Radiology, Knowledge and Information Systems, NeuroImage, Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE and HAL (Le Centre pour la Communication Scientifique Directe).

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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