Daniel Haehn

759 citations
31 papers · 357 · h-index 11

Impact in

    • Advanced Electron Microscopy Techniques and Applications
  • Biophysics top 5%
    • Cell Image Analysis Techniques
    • Advanced Fluorescence Microscopy Techniques

Papers in

Daniel Haehn

26 papers receiving 352 citations

Peers

Daniel Haehn
Comparison fields: 5 of 94
  • Structural Biology 32
  • Biophysics 82
  • Computer Vision and Pattern Recognition 110
  • Health Informatics 6
  • Cognitive Neuroscience 86
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Fenqiang Zhao United States
Amelio Vázquez-Reina United States
Suprosanna Shit Germany
Joseph J. Capowski United States
Kerry M. Brown United States
Yi Fei Cheng United States
Ali K. Al-Awami Saudi Arabia
N. Kasthuri India
Toufiq Parag United States
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Citations per year

Countries citing papers authored by Daniel Haehn

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Haehn

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 31 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201267
2 201837
3 201535
4 201532
5 201431
6 202024
7 201716
8
Fast Mitochondria Detection for Connectomics
202012
9 202012
10 201811
11 202010
12 201610
13 20139
14 20199
15 20148
16 20167
17 20176
18 20245
19 20234
20 20223

About Daniel Haehn

Daniel Haehn is a scholar working on Computer Vision and Pattern Recognition, Biophysics, Radiology, Nuclear Medicine and Imaging, Cognitive Neuroscience and Molecular Biology, having authored 31 papers that have together received 357 indexed citations. Recurring topics across this work include Cell Image Analysis Techniques (10 papers), Data Visualization and Analytics (5 papers), Functional Brain Connectivity Studies (4 papers), Advanced Neuroimaging Techniques and Applications (3 papers), Visual Attention and Saliency Detection (3 papers), Neural dynamics and brain function (3 papers), Advanced X-ray Imaging Techniques (2 papers) and Distributed and Parallel Computing Systems (2 papers). The work is most often cited by research in Structural Biology (32 citations), Biophysics (82 citations), Computer Vision and Pattern Recognition (110 citations), Health Informatics (6 citations) and Cognitive Neuroscience (86 citations). Daniel Haehn has collaborated with scholars based in United States, Switzerland and Saudi Arabia. Frequent co-authors include Hanspeter Pfister, James Tompkin, Jeff W. Lichtman, P. Ellen Grant, Narayanan Kasthuri, Johanna Beyer, Rudolph Pienaar, V.S. Caviness, April A. Benasich and Matthew Gregas. Their work appears in journals such as IEEE Transactions on Visualization and Computer Graphics, Microscopy and Microanalysis, Cerebral Cortex, Informatics and Journal of Biomedical Optics.

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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