Michael Schwier

20 papers receiving 535 citations

Peers

Michael Schwier
Comparison fields: 5 of 104
  • Health Informatics 15
  • Radiology, Nuclear Medicine and Imaging 221
  • Computer Vision and Pattern Recognition 130
  • Hepatology 42
  • Radiation 38
Replace Michael Suehling with:
Michael Suehling Germany
Laurent Massoptier Italy
Derek Merck United States
Hendrik Laue Germany
Marco Nolden Germany
Xiangrong Zhou Japan
Max Schöbinger Germany
Vincent Agnus France
Yoshiharu Higashida Japan
Tobias Boskamp Germany
Michael Schwier relative to Michael Suehling Germany Michael Suehling's profile →
Citations per field
00.5×2.7×
Michael Suehling · 1×
Citations per year

Countries citing papers authored by Michael Schwier

Since Specialization
Citations

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

Fields of papers citing papers by Michael Schwier

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 202326
2 201826
3 201835
4 20163
5 201637
6 20160
7 20167
8 201418
9 20141
10 201327
11 20135
12 201311
13 201119
14 2011245
15 201012
16
Object-oriented application development with MeVisLab and Python
200922
17 200916
18 200912
19 20085
20
[On the behavior mode of alkaline leukocyte phosphatase in childhood under physiological and pathological conditions].
19672

About Michael Schwier

Michael Schwier is a scholar working on Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition, Complementary and Manual Therapy, Radiology, Nuclear Medicine and Imaging and Artificial Intelligence, having authored 22 papers that have together received 551 indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (8 papers), AI in cancer detection (8 papers), Radiomics and Machine Learning in Medical Imaging (7 papers), Computer Graphics and Visualization Techniques (3 papers), Medical Imaging and Analysis (3 papers), MRI in cancer diagnosis (2 papers), Medical Imaging Techniques and Applications (2 papers) and Liver Disease Diagnosis and Treatment (2 papers). The work is most often cited by research in Health Informatics (15 citations), Radiology, Nuclear Medicine and Imaging (221 citations), Computer Vision and Pattern Recognition (130 citations), Hepatology (42 citations) and Radiation (38 citations). Michael Schwier has collaborated with scholars based in Germany, United States and Switzerland. Frequent co-authors include Heinz‐Otto Peitgen, André Homeyer, Hendrik Laue, Felix Ritter, Tobias Boskamp, Florian Link, Horst K. Hahn, Uta Dahmen, Olaf Dirsch and Tobias Gass. Their work appears in journals such as Investigative Radiology, International Journal of Computer Assisted Radiology and Surgery, Journal of Visualized Experiments, Computers in Biology and Medicine and International Journal for Numerical Methods in Biomedical Engineering.

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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