Jan Ehrhardt

2.8k citations
93 papers · 1.4k · h-index 21

Impact in

Papers in

Jan Ehrhardt

90 papers receiving 1.4k citations

Peers

Jan Ehrhardt
Comparison fields: 5 of 110
  • Radiation 368
  • Radiology, Nuclear Medicine and Imaging 630
  • Computer Vision and Pattern Recognition 419
  • Pulmonary and Respiratory Medicine 261
  • Health Informatics 9
Replace Floris Ernst with:
Floris Ernst Germany
Hideaki Haneishi Japan
Wolfgang Wein Germany
Xiaokun Liang China
Tzung-Chi Huang Taiwan
María J. Ledesma‐Carbayo Spain
Orçun Göksel Switzerland
Takayuki Ishida Japan
Jef Vandemeulebroucke Belgium
Jovan G. Brankov United States
Jan Ehrhardt relative to Floris Ernst Germany Floris Ernst's profile →
Citations per field
00.5×1.5×2.4×
Floris Ernst · 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 93 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2009118
2 2007110
3 201096
4 201859
5 201158
6 201256
7 201445
8 200141
9 200139
10 201335
11 200134
12 200831
13 200831
14 200429
15 200728
16 202027
17 200825
18 201423
19 200021
20 200720

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 93 papers that have together received 1.4k indexed citations. Recurring topics across this work include Medical Imaging Techniques and Applications (35 papers), Medical Image Segmentation Techniques (33 papers), Advanced Radiotherapy Techniques (25 papers), Lung Cancer Diagnosis and Treatment (16 papers), Radiomics and Machine Learning in Medical Imaging (14 papers), 3D Shape Modeling and Analysis (11 papers), Advanced MRI Techniques and Applications (9 papers) and AI in cancer detection (8 papers). The work is most often cited by research in Radiation (368 citations), Radiology, Nuclear Medicine and Imaging (630 citations), Computer Vision and Pattern Recognition (419 citations), Pulmonary and Respiratory Medicine (261 citations) and Health Informatics (9 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, Rainer Schmidt, S. J. Pöppl, W Plötz, Dennis Säring, Wei Lü, Daniel A. Low and Thorsten Frenzel. 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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