Matthew McAuliffe

49 papers receiving 2.0k citations

Peers

Matthew McAuliffe
Comparison fields: 5 of 153
  • Biophysics 366
  • Aging 66
  • Structural Biology 42
  • Radiology, Nuclear Medicine and Imaging 389
  • Computer Vision and Pattern Recognition 273
Replace Vannary Meas‐Yedid with:
Vannary Meas‐Yedid France
François Aguet United States
Allen Goodman United States
Carsten Marr Germany
Tim Becker Germany
Arrate Muñoz‐Barrutia Spain
A. Santos Spain
Ingo Roeder Germany
Ali Ertürk Germany
Etsuo A. Susaki Japan
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Citations per field
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Citations per year

Countries citing papers authored by Matthew McAuliffe

Since Specialization
Citations

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

Fields of papers citing papers by Matthew McAuliffe

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 51 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2002394
2 2013219
3 2007194
4 2014135
5 2007112
6 2007110
7 201298
8 200560
9 201058
10 201756
11
Image fusion using CT, MRI and PET for treatment planning, navigation and follow up in percutaneous RFA.
200954
12 201453
13 199547
14 201644
15 201638
16 200634
17 201933
18 201529
19 200124
20 198223

About Matthew McAuliffe

Matthew McAuliffe is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine, Biomedical Engineering and Biophysics, having authored 51 papers that have together received 2.0k indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (17 papers), Advanced Neural Network Applications (7 papers), Prostate Cancer Diagnosis and Treatment (7 papers), Cell Image Analysis Techniques (6 papers), Medical Imaging and Analysis (5 papers), Biomedical Text Mining and Ontologies (4 papers), Advanced Fluorescence Microscopy Techniques (3 papers) and Advanced Neuroimaging Techniques and Applications (3 papers). The work is most often cited by research in Biophysics (366 citations), Aging (66 citations), Structural Biology (42 citations), Radiology, Nuclear Medicine and Imaging (389 citations) and Computer Vision and Pattern Recognition (273 citations). Matthew McAuliffe has collaborated with scholars based in United States, India and Australia. Frequent co-authors include William Gandler, Delia P. McGarry, François Lalonde, Benes L. Trus, K.G. Csaky, Evan McCreedy, Zhirong Bao, Daniel A. Colón‐Ramos, Hari Shroff and Yicong Wu. Their work appears in journals such as International Journal of Radiation Oncology*Biology*Physics, Medical Physics, Journal of the American Medical Informatics Association, Data Science Journal and Journal of Vascular and Interventional Radiology.

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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