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Researcher · University of Graz · Austria

Kristian Bredies

Kristian Bredies publishes mostly in Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition and Computational Mechanics, on topics such as Sparse and Compressive Sensing Techniques, Numerical methods in inverse problems and Advanced MRI Techniques and Applications.

ORCID 0000-0001-7140-043X OpenAlex
World rank
#249,091
of 7,710,434 ranked researchers
Rank in Austria
#1,849
of 43,330
Works
180
Citations
6.2k
Citations per work
34.5
h-index
37
i10-index 62Top 6% in Radiology, Nuclear Medicine and Imaging
Kristian Bredies

What does Kristian Bredies research?

Kristian Bredies's work is mostly in Computer Science (21%), Medicine (19%), Engineering (18%).

Physical Sciences: 87 works · 48.4% of their workComputer Science: 38 works · 21.1% of their workComputer Vision and Pattern Recognition: 27 works · 14.8% of their workComputational Theory and Mathematics: 11 works · 6.3% of their workEngineering: 32 works · 17.9% of their workComputational Mechanics: 24 works · 13.2% of their workBiomedical Engineering: 8 works · 4.7% of their workMathematics: 17 works · 9.4% of their workMathematical Physics: 17 works · 9.4% of their workEverything else: 58 works · 32.5% of their workHealth Sciences: 34 works · 19.1% of their workMedicine: 34 works · 19.1% of their workRadiology, Nuclear Medicine and Imaging: 34 works · 19.1% of their workTHEIR WORKKristian Bredies180works
Physical Sciences48%Health Sciences19%

Their six largest subfields, inside their fields and domains; the grey slice is everything else they publish. The interactive view splits every one of their works down to single topics.

The fields and subfields, with their numbers
    1. Computer Science3821.1%
    2. Engineering3217.9%
    3. Mathematics179.4%
  2. Everything else5832.5%
    1. Medicine3419.1%
  1. 1Radiology, Nuclear Medicine and Imaging19% of their works
  2. 2Computer Vision and Pattern Recognition15% of their works
  3. 3Computational Mechanics13% of their works
  4. 4Mathematical Physics9% of their works
  5. 5Computational Theory and Mathematics6% of their works
  6. 6Biomedical Engineering5% of their works

Research topics

Which keywords describe Kristian Bredies's research?

The keywords of their largest research topics: Deep Learning, Compressed Sensing, Sparse Representation, Inverse Problems, Regularization Methods, Magnetic Resonance Imaging, Perfusion Imaging and Image Denoising.

Size is their works in the topics tagged with each word, from their 8 largest topics. Each links to the topic it comes from most. The words come from the keyword list OpenAlex gives each topic, not from the text of the papers, so a word can appear that none of the papers uses.

All 17 words, with their numbers
  1. Deep Learning833 topics
  2. Compressed Sensing471 topic
  3. Sparse Representation471 topic
  4. Inverse Problems381 topic
  5. Regularization Methods381 topic
  6. Magnetic Resonance Imaging351 topic
  7. Perfusion Imaging351 topic
  8. Image Denoising301 topic
  9. Sparse Representations301 topic
  10. Imaging291 topic
  11. PET/CT291 topic
  12. Image Segmentation181 topic
  13. Medical Image Analysis181 topic
  14. Iterative Algorithms121 topic
  15. Nonlinear Operators121 topic
  16. Photoacoustic Imaging101 topic
  17. Tomography101 topic

Where does Kristian Bredies work?

Kristian Bredies's main affiliation in the publication record is University of Graz, Austria.

How many publications and citations does Kristian Bredies have?

OpenAlex counts 180 works and 6,213 citations for Kristian Bredies, an h-index of 37, ranking #249,091 of 7,710,434 researchers worldwide on the quality score.

Ranked on field-normalised citation excellence (50%), output (30%) and citations (20%). Counts come from OpenAlex author records, which occasionally merge different people who share a name or split one person into several.

Papers, co-authors, who cited this work and researchers on the nearest topics have tabs of their own, above. Is this your page? Claim it with your ORCID iD, or request a correction or removal.

Discussion

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