Greg Ongie

23 papers receiving 747 citations

Greg Ongie's Hit Papers

Deep Learning Techniques for Inverse Problems in Imaging 2020 · 352 citations
3520+2+4Years since publication100200300

Peers

Greg Ongie
Comparison fields: 5 of 74
  • Acoustics and Ultrasonics 15
  • Computational Mechanics 352
  • Computer Vision and Pattern Recognition 288
  • Radiology, Nuclear Medicine and Imaging 256
  • Media Technology 67
Replace Ajil Jalal with:
Ajil Jalal United States
Clarice Poon United Kingdom
Vincent Duval France
Gilles Puy France
Yaniv Romano Israel
David M. Strong United States
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Citations per field
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Countries citing papers authored by Greg Ongie

Since Specialization
Citations

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

Fields of papers citing papers by Greg Ongie

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 17 scholars most cited alongside Greg Ongie, 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 Greg Ongie Line = papers co-authored together Greg Ongie links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Deep Learning Techniques for Inverse Problems in Imaging
Hit paper breakdown →
2020352
2 2019104
3 201681
4 201749
5 201443
6 201724
7 201521
8 201718
9 201517
10 201615
11 201515
12 20158
13 20166
14 20196
15 20175
16 20224
17 20172
18 20212
19 20201
20 20251

About Greg Ongie

Greg Ongie is a scholar working on Computational Mechanics, Computer Vision and Pattern Recognition, Biomedical Engineering, Radiology, Nuclear Medicine and Imaging and Geophysics, having authored 25 papers that have together received 778 indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (18 papers), Image and Signal Denoising Methods (11 papers), Medical Imaging Techniques and Applications (7 papers), Advanced X-ray and CT Imaging (5 papers), Photoacoustic and Ultrasonic Imaging (5 papers), Advanced MRI Techniques and Applications (5 papers), Radiation Dose and Imaging (3 papers) and Advanced Image Processing Techniques (3 papers). The work is most often cited by research in Acoustics and Ultrasonics (15 citations), Computational Mechanics (352 citations), Computer Vision and Pattern Recognition (288 citations), Radiology, Nuclear Medicine and Imaging (256 citations) and Media Technology (67 citations). Greg Ongie has collaborated with scholars based in United States and China. Frequent co-authors include Rebecca Willett, Mathews Jacob, Richard G. Baraniuk, Ajil Jalal, Christopher A. Metzler, Alexandros G. Dimakis, Sathish Ramani, Yue Hu, Laura Balzano and Robert D. Nowak. Their work appears in journals such as IEEE Transactions on Computational Imaging, IEEE Transactions on Medical Imaging, SIAM Journal on Imaging Sciences, IEEE Signal Processing Letters and IEEE Transactions on Image Processing.

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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