Neculai Archip

608 total citations
23 papers, 422 citations indexed

About

Neculai Archip is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Biomedical Engineering. According to data from OpenAlex, Neculai Archip has authored 23 papers receiving a total of 422 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Computer Vision and Pattern Recognition, 12 papers in Radiology, Nuclear Medicine and Imaging and 6 papers in Biomedical Engineering. Recurrent topics in Neculai Archip's work include Medical Image Segmentation Techniques (13 papers), Advanced MRI Techniques and Applications (6 papers) and Medical Imaging and Analysis (5 papers). Neculai Archip is often cited by papers focused on Medical Image Segmentation Techniques (13 papers), Advanced MRI Techniques and Applications (6 papers) and Medical Imaging and Analysis (5 papers). Neculai Archip collaborates with scholars based in United States, Canada and Switzerland. Neculai Archip's co-authors include Simon K. Warfield, Ferenc A. Jólesz, Alexandra J. Golby, Olivier Clatz, Robert Rohling, Peter McL. Black, Nikos Chrisochoides, Andriy Fedorov, Stephen Whalen and M. Egmont‐Petersen and has published in prestigious journals such as NeuroImage, Journal of Biomechanics and IEEE Transactions on Medical Imaging.

In The Last Decade

Neculai Archip

23 papers receiving 399 citations

Peers

Neculai Archip
Comparison fields: 5 of 73
  • Computer Vision and Pattern Recognition 205
  • Radiology, Nuclear Medicine and Imaging 200
  • Biomedical Engineering 146
  • Genetics 50
  • Surgery 36
Replace Grzegorz Soza with:
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Karen E. Lunn United States
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Citations per field, relative to Neculai Archip
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Citations per year, relative to Neculai Archip
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Countries citing papers authored by Neculai Archip

Since Specialization
Citations

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

Fields of papers citing papers by Neculai Archip

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Neculai Archip

This figure shows the co-authorship network connecting the top 25 collaborators of Neculai Archip. A scholar is included among the top collaborators of Neculai Archip based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Neculai Archip. Neculai Archip is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
# Work Indexed citations
1 17
2 7
3 31
4 25
5 119
6 23
7 3
8 28
9 1
10 8
11 8
12 14
13 22
14 1
15 1
16 2
17
A color image segmentation method based on seeded region growing and visual attention
4
18 1
19 58
20 4

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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