Matthew C. Murphy

3.7k citations
73 papers · 2.8k indexed · h-index 26

Impact in

Papers in

Matthew C. Murphy

70 papers receiving 2.8k citations

Peers

Matthew C. Murphy
Comparison fields: 5 of 135
  • Radiology, Nuclear Medicine and Imaging 1.3k
  • Cognitive Neuroscience 766
  • Neurology 173
  • Cellular and Molecular Neuroscience 368
  • Biomedical Engineering 872
Replace Curtis L. Johnson with:
Curtis L. Johnson United States
Alberto Prats‐Galino Spain
Weihong Yuan United States
Sophie Pezet France
Fatima Nasrallah Australia
Byung‐Jo Kim South Korea
Robert W. Prost United States
Hubertus Axer Germany
Wonhye Lee United States
Stephan Felber Austria
Matthew C. Murphy relative to Curtis L. Johnson United States Curtis L. Johnson's profile →
Citations per field
00.5×3.1×
Curtis L. Johnson · 1×
Citations per year

Countries citing papers authored by Matthew C. Murphy

Since Specialization
Citations

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

Fields of papers citing papers by Matthew C. Murphy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Matthew C. Murphy. 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 Matthew C. Murphy. The network helps show where Matthew C. Murphy may publish in the future.

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20251
2 20242
3 20248
4 20243
5 20243
6 20235
7 202330
8 20222
9 202242
10 20224
11 202025
12 20185
13 201724
14 20164
15 201671
16 2015166
17 201418
18 201322
19 201013
20 200112

About Matthew C. Murphy

Matthew C. Murphy is a scholar working on Radiology, Nuclear Medicine and Imaging, Cognitive Neuroscience, Neurology, Sensory Systems and Biomedical Engineering, having authored 73 papers that have together received 2.8k indexed citations. Recurring topics across this work include Ultrasound Imaging and Elastography (22 papers), Advanced MRI Techniques and Applications (16 papers), Advanced Neuroimaging Techniques and Applications (16 papers), Elasticity and Material Modeling (12 papers), Functional Brain Connectivity Studies (11 papers), Cerebrospinal fluid and hydrocephalus (6 papers), Visual perception and processing mechanisms (5 papers) and Dementia and Cognitive Impairment Research (5 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (1.3k citations), Cognitive Neuroscience (766 citations), Neurology (173 citations), Cellular and Molecular Neuroscience (368 citations) and Biomedical Engineering (872 citations). Matthew C. Murphy has collaborated with scholars based in United States, South Korea and China. Frequent co-authors include Richard L. Ehman, John Huston, Clifford R. Jack, Kevin J. Glaser, Armando Manduca, Joel P. Felmlee, Matthew L. Senjem, David T. Jones, Prashanthi Vemuri and Jeffrey L. Gunter. Their work appears in journals such as Journal of Magnetic Resonance Imaging, NeuroImage, Alzheimer s & Dementia, Journal of Molecular and Cellular Cardiology and Magnetic Resonance in Medicine.

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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