Iman Aganj

1.7k citations
59 papers · 1.1k · h-index 18

Impact in

Papers in

Iman Aganj

55 papers receiving 1.1k citations

Peers

Iman Aganj
Comparison fields: 5 of 99
  • Computational Mathematics 54
  • Radiology, Nuclear Medicine and Imaging 754
  • Structural Biology 31
  • Cognitive Neuroscience 307
  • Computer Vision and Pattern Recognition 163
Replace Daniel B. Ennis with:
Daniel B. Ennis United States
James G. Malcolm United States
A. Nabavi Germany
Matt G. Hall United Kingdom
Lisa Jonasson Switzerland
Philip Batchelor United Kingdom
Dirk H. J. Poot Netherlands
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Matthias Weigel Switzerland
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Citations per field
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Citations per year

Countries citing papers authored by Iman Aganj

Since Specialization
Citations

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

Fields of papers citing papers by Iman Aganj

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 59 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2010259
2 2011108
3 2015101
4 201860
5 200940
6 201738
7 200937
8 201934
9 201132
10 201231
11 201428
12 200828
13 201523
14 201120
15 201720
16 201719
17 202119
18 201118
19
Sex differences in the human connectome: 4-Tesla high angular resolution diffusion imaging (HARDI) tractography in 234 young adult twins
201114
20 201814

About Iman Aganj

Iman Aganj is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Cognitive Neuroscience, Pediatrics, Perinatology and Child Health and Artificial Intelligence, having authored 59 papers that have together received 1.1k indexed citations. Recurring topics across this work include Advanced Neuroimaging Techniques and Applications (34 papers), Advanced MRI Techniques and Applications (26 papers), Functional Brain Connectivity Studies (16 papers), Medical Image Segmentation Techniques (15 papers), Medical Imaging Techniques and Applications (11 papers), MRI in cancer diagnosis (6 papers), Fetal and Pediatric Neurological Disorders (5 papers) and Brain Tumor Detection and Classification (3 papers). The work is most often cited by research in Computational Mathematics (54 citations), Radiology, Nuclear Medicine and Imaging (754 citations), Structural Biology (31 citations), Cognitive Neuroscience (307 citations) and Computer Vision and Pattern Recognition (163 citations). Iman Aganj has collaborated with scholars based in United States, United Kingdom and Germany. Frequent co-authors include Guillermo Sapiro, Christophe Lenglet, Noam Harel, Essa Yacoub, Bruce Fischl, Kǎmil Uǧurbil, Paul M. Thompson, Mukesh G. Harisinghani, Ralph Weissleder and Neda Jahanshad. Their work appears in journals such as NeuroImage, Scientific Reports, Magnetic Resonance in Medicine, Human Brain Mapping and Frontiers in Neuroscience.

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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