Michael Merickel

1.2k citations
52 papers · 804 indexed · h-index 17

Impact in

Papers in

Michael Merickel

48 papers receiving 763 citations

Peers

Michael Merickel
Comparison fields: 5 of 122
  • Sensory Systems 78
  • Cellular and Molecular Neuroscience 199
  • Radiology, Nuclear Medicine and Imaging 231
  • Cognitive Neuroscience 162
  • Computer Vision and Pattern Recognition 126
Replace Yoshimichi Ejima with:
Yoshimichi Ejima Japan
Panos Z. Marmarelis United States
Guangshu Hu China
A. J. H. Vendrik Netherlands
Timothy J. Gawne United States
A. F. C. Infantosi Brazil
Paul Schmidt Germany
G. Baumgartner Switzerland
Ha Hong United States
R. Martin Arthur United States
Michael Merickel relative to Yoshimichi Ejima Japan Yoshimichi Ejima's profile →
Citations per field
00.5×1.5×1.9×
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-authorship network

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
#Work
1 20244
2 202111
3 20074
4 20050
5 20051
6 199511
7 199539
8 19945
9 199412
10 199310
11 199253
12 19924
13 199117
14 199110
15 19897
16 198986
17 198852
18 198859
19 198018
20 197424

About Michael Merickel

Michael Merickel is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Biophysics, Cellular and Molecular Neuroscience and Cognitive Neuroscience, having authored 52 papers that have together received 804 indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (18 papers), AI in cancer detection (9 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), Advanced MRI Techniques and Applications (5 papers) and Cerebrovascular and Carotid Artery Diseases (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 (231 citations), Cognitive Neuroscience (162 citations) and Computer Vision and Pattern Recognition (126 citations). Michael Merickel has collaborated with scholars based in United States, Sweden and Canada. Frequent co-authors include Stanley B. Kater, James R. Brookeman, R. G. F. Gray, John W. Snell, Edwin W. Rubel, Chris R. S. Kaneko, William T. Katz, Michael F. Brown, C R Ayers and Carlos R. Ayers. Their work appears in journals such as Computerized Medical Imaging and Graphics, Brain Research, Pattern Recognition, Experimental Neurology and Proceedings of the National Academy of Sciences.

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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