Timo Kohlberger

3.0k citations
21 papers · 1.2k · h-index 14

Impact in

Papers in

Timo Kohlberger

21 papers receiving 1.2k citations

Peers

Timo Kohlberger
Comparison fields: 5 of 124
  • Health Informatics 91
  • Computer Vision and Pattern Recognition 611
  • Radiology, Nuclear Medicine and Imaging 341
  • Biophysics 85
  • Artificial Intelligence 340
Replace Maximilian Baust with:
Maximilian Baust Germany
Diana Mateus France
Ekta Walia India
Liansheng Wang China
Amir A. Amini United States
Ilker Hacihaliloglu United States
Fritz Albregtsen Norway
Martin Urschler Austria
Jun Lian United States
Dimitris Maroulis Greece
Timo Kohlberger relative to Maximilian Baust Germany Maximilian Baust's profile →
Citations per field
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Citations per year

Countries citing papers authored by Timo Kohlberger

Since Specialization
Citations

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

Fields of papers citing papers by Timo Kohlberger

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2018253
2 2019195
3 2003145
4 2004118
5 200596
6 200691
7 201965
8 201248
9 201140
10 201133
11 200628
12 201225
13 200915
14 200513
15 201410
16 20047
17 20075
18 20115
19 20034
20 20122

About Timo Kohlberger

Timo Kohlberger is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Artificial Intelligence, Pulmonary and Respiratory Medicine and Biophysics, having authored 21 papers that have together received 1.2k indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (10 papers), Radiomics and Machine Learning in Medical Imaging (7 papers), Advanced Vision and Imaging (6 papers), AI in cancer detection (6 papers), Advanced Image Processing Techniques (4 papers), Advanced Neural Network Applications (3 papers), Lung Cancer Diagnosis and Treatment (2 papers) and Optical Coherence Tomography Applications (2 papers). The work is most often cited by research in Health Informatics (91 citations), Computer Vision and Pattern Recognition (611 citations), Radiology, Nuclear Medicine and Imaging (341 citations), Biophysics (85 citations) and Artificial Intelligence (340 citations). Timo Kohlberger has collaborated with scholars based in United States, Germany and United Kingdom. Frequent co-authors include Christoph Schnörr, Daniel Cremers, Jason Hipp, Martin C. Stumpe, Yun Liu, Andrés Bruhn, Joachim Weickert, Holger Nobach, Paul Ruhnau and Arash Mohtashamian. Their work appears in journals such as IEEE Transactions on Image Processing, Nature Medicine, Archives of Pathology & Laboratory Medicine, International Journal of Computer Vision and Journal of Pathology Informatics.

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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