Michael Merickel

1.2k citations
52 papers · 809 · h-index 17

Impact in

Papers in

Michael Merickel

48 papers receiving 769 citations

Peers

Michael Merickel
Comparison fields: 5 of 117
  • Sensory Systems 78
  • Cellular and Molecular Neuroscience 199
  • Radiology, Nuclear Medicine and Imaging 200
  • Cognitive Neuroscience 153
  • Developmental Biology 13
Replace Yoshimichi Ejima with:
Yoshimichi Ejima Japan
Timothy J. Gawne United States
Panos Z. Marmarelis United States
A. J. H. Vendrik Netherlands
Guangshu Hu China
Ha Hong United States
G. Baumgartner Switzerland
R. Martin Arthur United States
J. Kaufhold United States
Fenno P. Ottes Netherlands
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Citations per field
00.5×6.5×
Yoshimichi Ejima · 1×
Citations per year

Countries citing papers authored by Michael Merickel

Since Specialization
Citations

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

Fields of papers citing papers by Michael Merickel

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 52 papers — load more, or switch the sort, to bring in the rest.

#Work
1 198986
2 197869
3 198859
4 199254
5 198852
6 198040
7 199539
8 199336
9 197734
10 198830
11 198129
12 197424
13 200621
14 197818
15 198018
16 199117
17 200717
18 198714
19 199013
20 202112

About Michael Merickel

Michael Merickel is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Artificial Intelligence, Cellular and Molecular Neuroscience and Cognitive Neuroscience, having authored 52 papers that have together received 809 indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (18 papers), AI in cancer detection (8 papers), Image and Object Detection Techniques (6 papers), Neuroscience and Neural Engineering (6 papers), Digital Image Processing Techniques (6 papers), Neural dynamics and brain function (6 papers), Cerebrovascular and Carotid Artery Diseases (5 papers) and Advanced MRI Techniques and Applications (5 papers). The work is most often cited by research in Sensory Systems (78 citations), Cellular and Molecular Neuroscience (199 citations), Radiology, Nuclear Medicine and Imaging (200 citations), Cognitive Neuroscience (153 citations) and Developmental Biology (13 citations). Michael Merickel has collaborated with scholars based in United States, Czechia and Canada. Frequent co-authors include Stanley B. Kater, James R. Brookeman, John W. Snell, R. G. F. Gray, Dan H. Sanes, Edwin W. Rubel, Chris R. S. Kaneko, William T. Katz, Michael F. Brown and C R Ayers. Their work appears in journals such as Computerized Medical Imaging and Graphics, Brain Research, Pattern Recognition, Magnetic Resonance in Medicine and Journal of Graph Algorithms and Applications.

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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