Joy Matsui

603 citations
11 papers · 424 · h-index 8

Impact in

Papers in

Joy Matsui

11 papers receiving 422 citations

Peers

Joy Matsui
Comparison fields: 5 of 63
  • Radiology, Nuclear Medicine and Imaging 292
  • Computational Mathematics 6
  • Cognitive Neuroscience 126
  • Neurology 83
  • Pediatrics, Perinatology and Child Health 98
Replace Elizabeth Zakszewski with:
Elizabeth Zakszewski United States
Greg D. Parker United Kingdom
Daniel Franc United States
Zhexing Liu China
Jeroen Mollink United Kingdom
JL Lancaster United States
Yanqing Tang China
Marek Kubicki United States
Hikaru Fukutomi Japan
Tina Banks United Kingdom
Joy Matsui relative to Elizabeth Zakszewski United States Elizabeth Zakszewski's profile →
Citations per field
00.5×1.5×
Elizabeth Zakszewski · 1×
Citations per year

Countries citing papers authored by Joy Matsui

Since Specialization
Citations

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

Fields of papers citing papers by Joy Matsui

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

11 of 11 papers shown
#Work
1 2014197
2 201256
3 201452
4 201341
5 201537
6 201310
7 201110
8 201310
9 20156
10 20133
11 20222

About Joy Matsui

Joy Matsui is a scholar working on Radiology, Nuclear Medicine and Imaging, Cognitive Neuroscience, Cellular and Molecular Neuroscience, Pediatrics, Perinatology and Child Health and Molecular Biology, having authored 11 papers that have together received 424 indexed citations. Recurring topics across this work include Advanced Neuroimaging Techniques and Applications (10 papers), Advanced MRI Techniques and Applications (7 papers), Functional Brain Connectivity Studies (4 papers), Genetic Neurodegenerative Diseases (2 papers), Fetal and Pediatric Neurological Disorders (2 papers), Mitochondrial Function and Pathology (1 paper), Neuroscience and Music Perception (1 paper) and Cardiovascular Health and Disease Prevention (1 paper). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (292 citations), Computational Mathematics (6 citations), Cognitive Neuroscience (126 citations), Neurology (83 citations) and Pediatrics, Perinatology and Child Health (98 citations). Joy Matsui has collaborated with scholars based in United States, Chile and France. Frequent co-authors include Hans J. Johnson, Mahshid Farzinfar, Guido Gerig, Martin Styner, François Budin, İpek Oğuz, Zhexing Liu, Vincent A. Magnotta, Jane S. Paulsen and Jatin G. Vaidya. Their work appears in journals such as Frontiers in Neuroinformatics, Human Brain Mapping, Frontiers in Human Neuroscience, Brain Connectivity and International Journal of Geriatric Psychiatry.

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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