Kilian M. Pohl
- Radiology, Nuclear Medicine and Imaging top 1%
- Computer Vision and Pattern Recognition top 1%
- Cognitive Neuroscience top 2%
- Artificial Intelligence top 2%
- Psychiatry and Mental health top 5%
- Co-authors
- Edith V. SullivanAdolf PfefferbaumEhsan AdeliQingyu ZhaoWilliam M. WellsRon KikinisW. Eric L. GrimsonNatalie M. Zahr
- Topics
- Medical Image Segmentation Techniques (42 papers)Functional Brain Connectivity Studies (36 papers)Advanced Neuroimaging Techniques and Applications (35 papers)
- Journals
- Nature CommunicationsSHILAP Revista de lepidopterologíaIEEE Transactions on Pattern Analysis and Machine Intelligence
- Partner nations
- United StatesSouth KoreaFrance
In The Last Decade
Kilian M. Pohl
159 papers receiving 3.2k citations
Peers
Comparison fields: 5 of 150
- Radiology, Nuclear Medicine and Imaging 1.1k
- Computer Vision and Pattern Recognition 908
- Cognitive Neuroscience 887
- Artificial Intelligence 483
- Psychiatry and Mental health 397
Countries citing papers authored by Kilian M. Pohl
This map shows the geographic impact of Kilian M. Pohl'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 Kilian M. Pohl with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kilian M. Pohl more than expected).
Fields of papers citing papers by Kilian M. Pohl
This network shows the impact of papers produced by Kilian M. Pohl. 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 Kilian M. Pohl. The network helps show where Kilian M. Pohl may publish in the future.
Co-authorship network of co-authors of Kilian M. Pohl
This figure shows the co-authorship network connecting the top 25 collaborators of Kilian M. Pohl. A scholar is included among the top collaborators of Kilian M. Pohl 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 Kilian M. Pohl. Kilian M. Pohl is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 5 | |
| 4 | 0 | |
| 5 | 4 | |
| 6 | 15 | |
| 7 | 2 | |
| 8 | 1 | |
| 9 | 15 | |
| 10 | 5 | |
| 11 | 19 | |
| 12 | 3 | |
| 13 | 0 | |
| 14 | 20 | |
| 15 | 20 | |
| 16 | Variational Autoencoder with Truncated Mixture of Gaussians for Functional Connectivity Analysis | 1 |
| 17 | 15 | |
| 18 | 5 | |
| 19 | 7 | |
| 20 | 20 |
About Kilian M. Pohl
Kilian M. Pohl is a scholar working on Health Informatics, Virology and Radiology, Nuclear Medicine and Imaging, having authored 169 papers that have together received 3.3k indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (42 papers), Functional Brain Connectivity Studies (36 papers) and Advanced Neuroimaging Techniques and Applications (35 papers). The work is most often cited by research in Neurology (382 citations), Radiology, Nuclear Medicine and Imaging (1.1k citations) and Cognitive Neuroscience (887 citations). Kilian M. Pohl has collaborated with scholars based in United States, South Korea and France. Frequent co-authors include Edith V. Sullivan, Adolf Pfefferbaum, Ehsan Adeli, Qingyu Zhao, William M. Wells, Ron Kikinis, W. Eric L. Grimson, Natalie M. Zahr, John W. Fisher and Dongjin Kwon. Their work appears in journals such as Nature Communications, SHILAP Revista de lepidopterología and IEEE Transactions on Pattern Analysis and Machine Intelligence.
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.