Jakob Wasserthal
- Radiology, Nuclear Medicine and Imaging top 2%
- Biomedical Engineering
- Pediatrics, Perinatology and Child Health top 10%
- Cognitive Neuroscience top 10%
- Computer Vision and Pattern Recognition top 10%
- Co-authors
- Peter NeherKlaus Maier‐HeinHanns‐Christian BreitDaniel T. BollShan YangMichael BachAlexander SauterMartin Segeroth
- Topics
- Radiomics and Machine Learning in Medical Imaging (9 papers)Advanced Neuroimaging Techniques and Applications (6 papers)Advanced MRI Techniques and Applications (5 papers)
- Journals
- PLoS ONENeuroImageRadiology
- Partner nations
- SwitzerlandGermanyChile
In The Last Decade
Jakob Wasserthal
20 papers receiving 1.2k citations
Hit Papers
Peers
Comparison fields: 5 of 94
- Radiology, Nuclear Medicine and Imaging 867
- Biomedical Engineering 215
- Pediatrics, Perinatology and Child Health 157
- Cognitive Neuroscience 157
- Computer Vision and Pattern Recognition 118
Countries citing papers authored by Jakob Wasserthal
This map shows the geographic impact of Jakob Wasserthal'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 Jakob Wasserthal with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jakob Wasserthal more than expected).
Fields of papers citing papers by Jakob Wasserthal
This network shows the impact of papers produced by Jakob Wasserthal. 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 Jakob Wasserthal. The network helps show where Jakob Wasserthal may publish in the future.
Co-authorship network of co-authors of Jakob Wasserthal
This figure shows the co-authorship network connecting the top 25 collaborators of Jakob Wasserthal. A scholar is included among the top collaborators of Jakob Wasserthal 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 Jakob Wasserthal. Jakob Wasserthal is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 0 | |
| 3 | TotalSegmentator MRI: Robust Sequence-independent Segmentation of Multiple Anatomic Structures in MRIbreakdown → | 26 |
| 4 | 2 | |
| 5 | 0 | |
| 6 | 1 | |
| 7 | 1 | |
| 8 | 0 | |
| 9 | 6 | |
| 10 | 2 | |
| 11 | 6 | |
| 12 | 4 | |
| 13 | 4 | |
| 14 | 4 | |
| 15 | 29 | |
| 16 | 9 | |
| 17 | 11 | |
| 18 | 61 | |
| 19 | 116 | |
| 20 | TractSeg - Fast and accurate white matter tract segmentationbreakdown → | 373 |
About Jakob Wasserthal
Jakob Wasserthal is a scholar working on Health Informatics, Radiology, Nuclear Medicine and Imaging and Neurology, having authored 23 papers that have together received 1.2k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (9 papers), Advanced Neuroimaging Techniques and Applications (6 papers) and Advanced MRI Techniques and Applications (5 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (867 citations), Health Informatics (40 citations) and Computational Mathematics (13 citations). Jakob Wasserthal has collaborated with scholars based in Switzerland, Germany and Chile. Frequent co-authors include Peter Neher, Klaus Maier‐Hein, Hanns‐Christian Breit, Daniel T. Boll, Shan Yang, Michael Bach, Alexander Sauter, Martin Segeroth, Joshy Cyriac and Maurice Pradella. Their work appears in journals such as PLoS ONE, NeuroImage and Radiology.
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.