Oliver Gloger

1.2k total citations
11 papers, 161 citations indexed

About

Oliver Gloger is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Epidemiology. According to data from OpenAlex, Oliver Gloger has authored 11 papers receiving a total of 161 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Computer Vision and Pattern Recognition, 7 papers in Radiology, Nuclear Medicine and Imaging and 2 papers in Epidemiology. Recurrent topics in Oliver Gloger's work include Medical Image Segmentation Techniques (6 papers), MRI in cancer diagnosis (5 papers) and Advanced Neural Network Applications (5 papers). Oliver Gloger is often cited by papers focused on Medical Image Segmentation Techniques (6 papers), MRI in cancer diagnosis (5 papers) and Advanced Neural Network Applications (5 papers). Oliver Gloger collaborates with scholars based in Germany. Oliver Gloger's co-authors include Henry Völzke, Klaus Tönnies, René Laqua, Jens‐Peter Kühn, Ralf Puls, Volkmar Liebscher, Robin Bülow, Birger Mensel, Eike Nagel and Matthias Ehrhardt and has published in prestigious journals such as IEEE Transactions on Biomedical Engineering, IEEE Transactions on Medical Imaging and Pattern Recognition.

In The Last Decade

Oliver Gloger

11 papers receiving 156 citations

Peers

Oliver Gloger

CVPR

RNMI

PRM

M Aparicio Italy

Jianwei Lin China

Ho Hin Lee United States

Seyed Raein Hashemi United States

Xiaowu Liu China

Bishesh Khanal United Kingdom

Khalaf Alshamrani Saudi Arabia

Raphaël Prevost France

Rafael T. Sousa Brazil

Hariharan Ravishankar India

M Aparicio Italy

Oliver Gloger

38 ×0.5

CVPR

65 ×1.0

RNMI

10 ×0.2

67 ×2.1

PRM

34 ×1.2

Citations per year, relative to Oliver Gloger Oliver Gloger (= 1×) peers M Aparicio

Countries citing papers authored by Oliver Gloger

Since Specialization

Citations

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

Fields of papers citing papers by Oliver Gloger

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Oliver Gloger

This figure shows the co-authorship network connecting the top 25 collaborators of Oliver Gloger. A scholar is included among the top collaborators of Oliver Gloger 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 Oliver Gloger. Oliver Gloger is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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11 of 11 papers shown

Gloger, Oliver & Klaus Tönnies. (2018). Subject-Specific prior shape knowledge in feature-oriented probability maps for fully automatized liver segmentation in MR volume data. Pattern Recognition. 84. 288–300. 7 indexed citations

Gloger, Oliver, Robin Bülow, Klaus Tönnies, & Henry Völzke. (2017). Automatic gallbladder segmentation using combined 2D and 3D shape features to perform volumetric analysis in native and secretin-enhanced MRCP sequences. Magnetic Resonance Materials in Physics Biology and Medicine. 31(3). 383–397. 6 indexed citations

Gloger, Oliver, Klaus Tönnies, Robin Bülow, & Henry Völzke. (2017). Automatized spleen segmentation in non-contrast-enhanced MR volume data using subject-specific shape priors. Physics in Medicine and Biology. 62(14). 5861–5883. 6 indexed citations

Gloger, Oliver, Klaus Tönnies, Birger Mensel, & Henry Völzke. (2015). Fully automatized renal parenchyma volumetry using a support vector machine based recognition system for subject-specific probability map generation in native MR volume data. Physics in Medicine and Biology. 60(22). 8675–8693. 8 indexed citations

Toennies, Klaus D., Oliver Gloger, Marko Rak, et al.. (2015). Image analysis in epidemiological applications. it - Information Technology. 57(1). 22–29. 3 indexed citations

Gloger, Oliver, Klaus Tönnies, René Laqua, & Henry Völzke. (2015). Fully Automated Renal Tissue Volumetry in MR Volume Data Using Prior-Shape-Based Segmentation in Subject-Specific Probability Maps. IEEE Transactions on Biomedical Engineering. 62(10). 2338–2351. 14 indexed citations

Gloger, Oliver, Volkmar Liebscher, Klaus Tönnies, & Henry Völzke. (2014). Fully Automatic Renal Parenchyma Volumetry in LDA-based Probability Maps Using Variational Outer Cortex Edge Alignment Forces.. 1207–1218. 1 indexed citations

Gloger, Oliver, et al.. (2014). Fully Automated Glottis Segmentation in Endoscopic Videos Using Local Color and Shape Features of Glottal Regions. IEEE Transactions on Biomedical Engineering. 62(3). 795–806. 33 indexed citations

Gloger, Oliver, et al.. (2011). Prior Shape Level Set Segmentation on Multistep Generated Probability Maps of MR Datasets for Fully Automatic Kidney Parenchyma Volumetry. IEEE Transactions on Medical Imaging. 31(2). 312–325. 33 indexed citations

10.

Gloger, Oliver, et al.. (2010). A fully automatic three-step liver segmentation method on LDA-based probability maps for multiple contrast MR images. Magnetic Resonance Imaging. 28(6). 882–897. 42 indexed citations

11.

Gloger, Oliver, Matthias Ehrhardt, Thore Dietrich, et al.. (2009). A threestepped coordinated level set segmentation method for identifying atherosclerotic plaques on MR‐images. Communications in Numerical Methods in Engineering. 25(6). 615–638. 8 indexed citations

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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