Mikkel B. Stegmann

27 papers receiving 735 citations

Peers

Mikkel B. Stegmann
Comparison fields: 5 of 89
  • Computer Vision and Pattern Recognition 482
  • Radiology, Nuclear Medicine and Imaging 335
  • Artificial Intelligence 176
  • Biomedical Engineering 97
  • Pulmonary and Respiratory Medicine 96
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Countries citing papers authored by Mikkel B. Stegmann

Since Specialization
Citations

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

Fields of papers citing papers by Mikkel B. Stegmann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mikkel B. Stegmann. 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 Mikkel B. Stegmann. The network helps show where Mikkel B. Stegmann may publish in the future.

Co-authorship network of co-authors of Mikkel B. Stegmann

This figure shows the co-authorship network connecting the top 25 collaborators of Mikkel B. Stegmann. A scholar is included among the top collaborators of Mikkel B. Stegmann based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Mikkel B. Stegmann. Mikkel B. Stegmann is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 14
2 20
3 28
4 28
5
Corpus Callosum Partitioning Schemes and Their Effect on Callosal Morphometry
4
6 362
7
The IMM Frontal Face Database
4
8 24
9 33
10 12
11
Unsupervised Correction of Physiologically-induced Slice-offsets in 4D Cardiac MRI
2
12
Generative Interpretation of Medical Images
17
13
Fast Registration of Cardiac Perfusion MRI
9
14
Automated Analysis of Corpora Callosa
4
15
Tracking Eyes using Shape and Appearance
5
16
Analysis and Segmentation of Face Images using Point Annotations and Linear Subspace Techniques
30
17
On exploiting wavelet bases in statistical region-based segmentation
2
18
Extending and applying active appearance models for automated, high precision segmentation in different image modalities
27
19
Object tracking using active appearance models
31
20
Automated Segmentation of Cardiac Magnetic Resonance Images
5

About Mikkel B. Stegmann

Mikkel B. Stegmann is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Signal Processing, having authored 27 papers that have together received 792 indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (15 papers), Face recognition and analysis (8 papers) and Face and Expression Recognition (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (482 citations), Radiology, Nuclear Medicine and Imaging (335 citations) and Health Informatics (8 citations). Mikkel B. Stegmann has collaborated with scholars based in Denmark, Germany and United Kingdom. Frequent co-authors include Bram van Ginneken, Marco Loog, Rasmus Larsen, Mads Larsen, Karl Sjöstrand, Bjarne Kjær Ersbøll, Dorthe Pedersen, Søren Ingvor Olsen, Charlotte Ryberg and Søren Forchhammer. Their work appears in journals such as Medical Image Analysis, IEEE Transactions on Information Forensics and Security and Computer Vision and Image Understanding.

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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