Jan Ehrhardt

2.8k citations
139 papers · 1.9k · h-index 23

Impact in

Papers in

Jan Ehrhardt

131 papers receiving 1.8k citations

Peers

Jan Ehrhardt
Comparison fields: 5 of 115
  • Radiation 442
  • Radiology, Nuclear Medicine and Imaging 835
  • Computer Vision and Pattern Recognition 620
  • Health Informatics 18
  • Pulmonary and Respiratory Medicine 322
Replace René Werner with:
René Werner Germany
Vladimír Pekar Germany
Jovan G. Brankov United States
María J. Ledesma‐Carbayo Spain
Wolfgang Wein Germany
Floris Ernst Germany
Zhanli Hu China
Tina Kapur United States
Liyuan Chen China
Soumya Ghose United States
Jan Ehrhardt relative to René Werner Germany René Werner's profile →
Citations per field
00.5×1.5×
René Werner · 1×
Citations per year

Countries citing papers authored by Jan Ehrhardt

Since Specialization
Citations

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

Fields of papers citing papers by Jan Ehrhardt

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Jan Ehrhardt, 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 Jan Ehrhardt Line = papers co-authored together Jan Ehrhardt links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 139 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2009130
2 2007120
3 2010115
4 201177
5 201870
6 201767
7 201264
8 201450
9 200148
10 200143
11 201342
12 200840
13 200140
14 200436
15 200833
16 200831
17 200728
18 201728
19 202228
20 200924

About Jan Ehrhardt

Jan Ehrhardt is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Radiation, Pulmonary and Respiratory Medicine and Computational Mechanics, having authored 139 papers that have together received 1.9k indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (56 papers), Medical Imaging Techniques and Applications (54 papers), Advanced Radiotherapy Techniques (33 papers), Lung Cancer Diagnosis and Treatment (26 papers), Radiomics and Machine Learning in Medical Imaging (19 papers), 3D Shape Modeling and Analysis (17 papers), AI in cancer detection (14 papers) and Advanced MRI Techniques and Applications (10 papers). The work is most often cited by research in Radiation (442 citations), Radiology, Nuclear Medicine and Imaging (835 citations), Computer Vision and Pattern Recognition (620 citations), Health Informatics (18 citations) and Pulmonary and Respiratory Medicine (322 citations). Jan Ehrhardt has collaborated with scholars based in Germany, United States and France. Frequent co-authors include Heinz Handels, René Werner, Alexander Schmidt-Richberg, Matthias Wilms, Siegfried J. Pöppl, Dennis Säring, Rainer Schmidt, W Plötz, Daniel A. Low and Wei Lü. Their work appears in journals such as Methods of Information in Medicine, International Journal of Computer Assisted Radiology and Surgery, Physics in Medicine and Biology, Medical Image Analysis and International Journal of Medical Informatics.

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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