Johannes Ulén
- Radiology, Nuclear Medicine and Imaging top 5%
- Pulmonary and Respiratory Medicine
- Biomedical Engineering
- Artificial Intelligence
- Physiology
- Co-authors
- Olof EnqvistElin TrägårdhLars EdenbrandtReza KabotehPablo BorrelliMay SadikPoul Flemming Høilund‐CarlsenMads Hvid Poulsen
- Topics
- Radiomics and Machine Learning in Medical Imaging (18 papers)Medical Imaging Techniques and Applications (13 papers)Prostate Cancer Treatment and Research (8 papers)
- Cited by
- Health InformaticsRadiology, Nuclear Medicine and ImagingPulmonary and Respiratory Medicine
- Journals
- SHILAP Revista de lepidopterologíaScientific ReportsPattern Recognition Letters
In The Last Decade
Johannes Ulén
28 papers receiving 460 citations
Peers
Comparison fields: 5 of 61
- Radiology, Nuclear Medicine and Imaging 330
- Pulmonary and Respiratory Medicine 183
- Biomedical Engineering 127
- Artificial Intelligence 51
- Physiology 37
Countries citing papers authored by Johannes Ulén
This map shows the geographic impact of Johannes Ulén'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 Johannes Ulén with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Johannes Ulén more than expected).
Fields of papers citing papers by Johannes Ulén
This network shows the impact of papers produced by Johannes Ulén. 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 Johannes Ulén. The network helps show where Johannes Ulén may publish in the future.
Co-authorship network of co-authors of Johannes Ulén
This figure shows the co-authorship network connecting the top 25 collaborators of Johannes Ulén. A scholar is included among the top collaborators of Johannes Ulén 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 Johannes Ulén. Johannes Ulén is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 8 | |
| 6 | 24 | |
| 7 | 23 | |
| 8 | 4 | |
| 9 | 7 | |
| 10 | 4 | |
| 11 | 8 | |
| 12 | 9 | |
| 13 | 35 | |
| 14 | 66 | |
| 15 | 19 | |
| 16 | 23 | |
| 17 | 30 | |
| 18 | Artificial Intelligence Based Method for Automated PET/CT Measurements of Prostate Gland Volume and Choline Uptake | 1 |
| 19 | 18 | |
| 20 | Good Features for Reliable Registration in Multi-Atlas Segmentation | 9 |
About Johannes Ulén
Johannes Ulén is a scholar working on Radiology, Nuclear Medicine and Imaging, Geriatrics and Gerontology and Pulmonary and Respiratory Medicine, having authored 29 papers that have together received 467 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (18 papers), Medical Imaging Techniques and Applications (13 papers) and Prostate Cancer Treatment and Research (8 papers). The work is most often cited by research in Health Informatics (21 citations), Radiology, Nuclear Medicine and Imaging (330 citations) and Pulmonary and Respiratory Medicine (183 citations). Johannes Ulén has collaborated with scholars based in Sweden, Denmark and India. Frequent co-authors include Olof Enqvist, Elin Trägårdh, Lars Edenbrandt, Reza Kaboteh, Pablo Borrelli, May Sadik, Poul Flemming Høilund‐Carlsen, Mads Hvid Poulsen, Jane Angel Simonsen and Henrik Kjölhede. Their work appears in journals such as SHILAP Revista de lepidopterología, Scientific Reports and Pattern Recognition Letters.
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.