Claes Lundström

2.1k citations
64 papers · 1.3k indexed · h-index 20

Impact in

Papers in

Claes Lundström

58 papers receiving 1.3k citations

Peers

Claes Lundström
Comparison fields: 5 of 132
  • Health Informatics 113
  • Computer Graphics and Computer-Aided Design 267
  • Computer Vision and Pattern Recognition 518
  • Biophysics 127
  • Radiology, Nuclear Medicine and Imaging 444
Replace Maximilian Baust with:
Maximilian Baust Germany
Chu Han China
L. Rodney Long United States
Andrea Schenk Germany
Bohyoung Kim South Korea
Liansheng Wang China
Akinobu Shimizu Japan
Jeongjin Lee South Korea
Kai Lawonn Germany
Jixiang Guo China
Claes Lundström relative to Maximilian Baust Germany Maximilian Baust's profile →
Citations per field
00.5×3.2×
Maximilian Baust · 1×
Citations per year

Countries citing papers authored by Claes Lundström

Since Specialization
Citations

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

Fields of papers citing papers by Claes Lundström

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20231
2 20231
3 20237
4 202219
5 202216
6 202218
7 202120
8 202012
9 202013
10 20195
11 20191
12 201921
13 201849
14 20176
15 20141
16 2014124
17 201243
18 200660
19 200691
20 200435

About Claes Lundström

Claes Lundström is a scholar working on Health Informatics, Computer Graphics and Computer-Aided Design, Biophysics, Computer Vision and Pattern Recognition and Radiology, Nuclear Medicine and Imaging, having authored 64 papers that have together received 1.3k indexed citations. Recurring topics across this work include AI in cancer detection (26 papers), Computer Graphics and Visualization Techniques (14 papers), Radiomics and Machine Learning in Medical Imaging (14 papers), Cell Image Analysis Techniques (9 papers), Medical Image Segmentation Techniques (7 papers), Artificial Intelligence in Healthcare and Education (7 papers), 3D Shape Modeling and Analysis (7 papers) and Digital Imaging in Medicine (5 papers). The work is most often cited by research in Health Informatics (113 citations), Computer Graphics and Computer-Aided Design (267 citations), Computer Vision and Pattern Recognition (518 citations), Biophysics (127 citations) and Radiology, Nuclear Medicine and Imaging (444 citations). Claes Lundström has collaborated with scholars based in Sweden, United Kingdom and United States. Frequent co-authors include Anders Ynnerman, Patric Ljung, Jesper Molin, Anders Persson, Gabriel Eilertsen, Jonas Unger, Sten Thorstenson, Darren Treanor, Joel Hedlund and Ken Museth. Their work appears in journals such as Journal of Pathology Informatics, IEEE Transactions on Visualization and Computer Graphics, Histopathology, Journal of Digital Imaging and Computerized Medical Imaging and Graphics.

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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