Hessam Sokooti

1.5k citations
8 papers · 609 indexed · 1 hit paper · h-index 6

Hessam Sokooti

8 papers receiving 597 citations

Hit Papers

A deep learning framework for unsupervised affine and def...4922018202620202023100200300400

Peers

Hessam Sokooti
Comparison fields: 5 of 77
  • Computer Vision and Pattern Recognition 346
  • Radiology, Nuclear Medicine and Imaging 341
  • Radiation 71
  • Health Informatics 10
  • Neurology 42
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

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

All Works

8 of 8 papers shown
#Work
1 20242
2 20244
3 20235
4 20219
5 201927
6 201947
7
A deep learning framework for unsupervised affine and deformable image registrationbreakdown →
2018492
8 201623

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), Medical Imaging Techniques and Applications (2 papers), Coronary Interventions and Diagnostics (2 papers), Medical Image Segmentation Techniques (2 papers), Advanced X-ray and CT Imaging (2 papers), Cardiovascular Disease and Adiposity (1 paper) and Surgical Simulation and Training (1 paper). 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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