Hessam Sokooti

1.5k citations
8 papers · 609 indexed · 1 hit paper · h-index 6
Topics
Cardiac Imaging and Diagnostics (3 papers)Radiomics and Machine Learning in Medical Imaging (2 papers)Medical Imaging Techniques and Applications (2 papers)

In The Last Decade

Hessam Sokooti

8 papers receiving 597 citations

Hit Papers

A deep learning framework for unsupervised affine and def...20182026202020232018100200300400

Peers

Hessam Sokooti
Comparison fields: 5 of 77
  • Computer Vision and Pattern Recognition 346
  • Radiology, Nuclear Medicine and Imaging 341
  • Biomedical Engineering 169
  • Artificial Intelligence 86
  • Radiation 71
Replace Floris F. Berendsen with:
Floris F. Berendsen Netherlands
Yeqin Shao China
Manav Bhushan United Kingdom
Bartłomiej W. Papież United Kingdom
Koen A. J. Eppenhof Netherlands
Bo Zhan China
Yicheng Wu China
Dzhoshkun I. Shakir United Kingdom
Junyu Chen United States
Junfeng Zhang China
Hessam Sokooti relative to Floris F. Berendsen Netherlands Floris F. Berendsen's profile →
Citations per field
00.5×1.5×
Floris F. Berendsen · 1×
Citations per year

Countries citing papers authored by Hessam Sokooti

Since Specialization
Citations

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

Fields of papers citing papers by Hessam Sokooti

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hessam Sokooti

This figure shows the co-authorship network connecting the top 25 collaborators of Hessam Sokooti. A scholar is included among the top collaborators of Hessam Sokooti 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 Hessam Sokooti. Hessam Sokooti is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

8 of 8 papers shown
#WorkIndexed citations
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2 4
3 5
4 9
5 27
6 47
7
A deep learning framework for unsupervised affine and deformable image registrationbreakdown →
492
8 23

About Hessam Sokooti

Hessam Sokooti is a scholar working on Radiology, Nuclear Medicine and Imaging, Radiation and Computer Vision and Pattern Recognition, having authored 8 papers that have together received 609 indexed citations. Recurring topics across this work include Cardiac Imaging and Diagnostics (3 papers), Radiomics and Machine Learning in Medical Imaging (2 papers) and Medical Imaging Techniques and Applications (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (346 citations), Radiology, Nuclear Medicine and Imaging (341 citations) and Radiation (71 citations). Hessam Sokooti has collaborated with scholars based in Netherlands, United Kingdom and Ireland. Frequent co-authors include Marius Staring, Ivana Išgum, Max A. Viergever, Floris F. Berendsen, Bob D. de Vos, Boudewijn P. F. Lelieveldt, Ben Glocker, Görkem Saygılı, Corrie A.M. Marijnen and Luca Incrocci. Their work appears in journals such as IEEE Access, Medical Physics and Medical Image Analysis.

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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