Tryphon Lambrou

1.4k citations
40 papers · 1.1k · h-index 15

Impact in

Papers in

Tryphon Lambrou

38 papers receiving 1.0k citations

Peers

Tryphon Lambrou
Comparison fields: 5 of 102
  • Neurology 385
  • Computer Vision and Pattern Recognition 457
  • Radiology, Nuclear Medicine and Imaging 252
  • Artificial Intelligence 194
  • Signal Processing 62
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Darko Zikic United States
Tom Brosch Germany
Majid Harouni Iran
Meng Ding China
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Boqiang Liu China
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Citations per year

Countries citing papers authored by Tryphon Lambrou

Since Specialization
Citations

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

Fields of papers citing papers by Tryphon Lambrou

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 40 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016252
2 2018184
3 200282
4 201360
5 201150
6 201850
7 202238
8 201138
9 201636
10 201631
11 200530
12 201725
13 201819
14 201119
15 200716
16
Brain Tumour Grading in Different MRI Protocols using SVM on Statistical Features.
201411
17 200911
18
Automatic segmentation of liver using a topology adaptive snake
200410
19 20119
20 20059

About Tryphon Lambrou

Tryphon Lambrou is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Artificial Intelligence, Neurology and Biomedical Engineering, having authored 40 papers that have together received 1.1k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (13 papers), Medical Image Segmentation Techniques (11 papers), Brain Tumor Detection and Classification (7 papers), Advanced Neural Network Applications (5 papers), Advanced MRI Techniques and Applications (5 papers), Advanced X-ray and CT Imaging (4 papers), Medical Imaging Techniques and Applications (4 papers) and Fetal and Pediatric Neurological Disorders (4 papers). The work is most often cited by research in Neurology (385 citations), Computer Vision and Pattern Recognition (457 citations), Radiology, Nuclear Medicine and Imaging (252 citations), Artificial Intelligence (194 citations) and Signal Processing (62 citations). Tryphon Lambrou has collaborated with scholars based in United Kingdom, United States and Spain. Frequent co-authors include Xujiong Ye, N.M. Allinson, Mohammadreza Soltaninejad, Guang Yang, Thomas R. Barrick, Franklyn A. Howe, Timothy L. Jones, Lei Zhang, A. D. Linney and Robert Speller. Their work appears in journals such as European Journal of Nuclear Medicine and Molecular Imaging, International Journal of Computer Assisted Radiology and Surgery, Physics in Medicine and Biology, IEEE Transactions on Medical Imaging and 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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