Peter Rogelj

807 total citations
35 papers, 555 citations indexed

About

Peter Rogelj is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Cognitive Neuroscience. According to data from OpenAlex, Peter Rogelj has authored 35 papers receiving a total of 555 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Computer Vision and Pattern Recognition, 12 papers in Radiology, Nuclear Medicine and Imaging and 7 papers in Cognitive Neuroscience. Recurrent topics in Peter Rogelj's work include Medical Image Segmentation Techniques (16 papers), MRI in cancer diagnosis (8 papers) and Advanced Image and Video Retrieval Techniques (7 papers). Peter Rogelj is often cited by papers focused on Medical Image Segmentation Techniques (16 papers), MRI in cancer diagnosis (8 papers) and Advanced Image and Video Retrieval Techniques (7 papers). Peter Rogelj collaborates with scholars based in Slovenia, Croatia and Norway. Peter Rogelj's co-authors include Stanislav Kovačič, James C. Gee, Saša Vlahinić, Frank G. Zöllner, Arvid Lundervold, María J. Ledesma‐Carbayo, Jarle Rørvik, A. Santos, Primož Petrič and Robert Hudej and has published in prestigious journals such as IEEE Access, Sensors and Radiotherapy and Oncology.

In The Last Decade

Peter Rogelj

32 papers receiving 526 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Peter Rogelj Slovenia 10 283 213 79 75 72 35 555
Lichi Zhang China 17 382 1.3× 227 1.1× 113 1.4× 39 0.5× 7 0.1× 69 921
Dzhoshkun I. Shakir United Kingdom 9 221 0.8× 160 0.8× 105 1.3× 43 0.6× 4 0.1× 22 532
Christian F. Baumgartner Germany 13 327 1.2× 130 0.6× 129 1.6× 40 0.5× 10 0.1× 30 696
Mark Hastenteufel Germany 7 230 0.8× 166 0.8× 159 2.0× 36 0.5× 5 0.1× 19 505
Tobias Kunert Germany 7 235 0.8× 157 0.7× 134 1.7× 27 0.4× 5 0.1× 13 484
Thomas Böttger Germany 4 213 0.8× 128 0.6× 125 1.6× 25 0.3× 5 0.1× 5 428
Jens Guehring Germany 15 552 2.0× 245 1.2× 78 1.0× 8 0.1× 8 0.1× 34 890
Karsten Østergaard Noe Denmark 9 227 0.8× 83 0.4× 71 0.9× 204 2.7× 70 1.0× 14 416
Alessandro Crimi Switzerland 13 234 0.8× 196 0.9× 106 1.3× 12 0.2× 8 0.1× 48 623
Hessam Sokooti Netherlands 6 341 1.2× 346 1.6× 169 2.1× 71 0.9× 3 0.0× 8 609

Countries citing papers authored by Peter Rogelj

Since Specialization
Citations

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

Fields of papers citing papers by Peter Rogelj

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Peter Rogelj

This figure shows the co-authorship network connecting the top 25 collaborators of Peter Rogelj. A scholar is included among the top collaborators of Peter Rogelj 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 Peter Rogelj. Peter Rogelj 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
1.
Žnidaršič, Anja, et al.. (2025). The complexity of caffeine's effects on regular coffee consumers. Heliyon. 11(2). e41471–e41471. 2 indexed citations
2.
Rogelj, Peter, et al.. (2025). Deep Learning for Brain MRI Tissue and Structure Segmentation: A Comprehensive Review. Algorithms. 18(10). 636–636.
3.
Vlahinić, Saša, et al.. (2024). A Framework for Evaluating Dynamic Directed Brain Connectivity Estimation Methods Using Synthetic EEG Signal Generation. Algorithms. 17(11). 517–517. 1 indexed citations
4.
Rogelj, Peter, et al.. (2024). Exploring Mathematical Decision-Making Through EEG Analysis. 69–72.
5.
Oblak, Janja Pretnar, et al.. (2024). Integrating EEG and Machine Learning to Analyze Brain Changes during the Rehabilitation of Broca’s Aphasia. Sensors. 24(2). 329–329. 2 indexed citations
6.
Vlahinić, Saša, et al.. (2022). Complex Pearson Correlation Coefficient for EEG Connectivity Analysis. Sensors. 22(4). 1477–1477. 77 indexed citations
7.
Vlahinić, Saša, et al.. (2022). Dynamic Connectivity Analysis Using Adaptive Window Size. Sensors. 22(14). 5162–5162. 5 indexed citations
8.
Drevenšek, Gorazd, et al.. (2022). Assessment of Model Accuracy in Eyes Open and Closed EEG Data: Effect of Data Pre-Processing and Validation Methods. Bioengineering. 10(1). 42–42. 6 indexed citations
9.
Drevenšek, Gorazd, et al.. (2021). Generation of Oscillatory Synthetic Signal Simulating Brain Network Dynamics. 141–146. 3 indexed citations
10.
Zöllner, Frank G., et al.. (2019). Image registration in dynamic renal MRI—current status and prospects. Magnetic Resonance Materials in Physics Biology and Medicine. 33(1). 33–48. 20 indexed citations
11.
Petrič, Primož, Robert Hudej, Peter Rogelj, et al.. (2013). Uncertainties of target volume delineation in MRI guided adaptive brachytherapy of cervix cancer: A multi-institutional study. Radiotherapy and Oncology. 107(1). 6–12. 74 indexed citations
12.
Petrič, Primož, Robert Hudej, Peter Rogelj, et al.. (2012). Comparison of 3D MRI with high sampling efficiency and 2D multiplanar MRI for contouring in cervix cancer brachytherapy. Radiology and Oncology. 46(3). 242–51. 21 indexed citations
13.
Zöllner, Frank G., Peter Rogelj, María J. Ledesma‐Carbayo, et al.. (2009). Assessment of 3D DCE-MRI of the kidneys using non-rigid image registration and segmentation of voxel time courses. Computerized Medical Imaging and Graphics. 33(3). 171–181. 93 indexed citations
14.
Rogelj, Peter & Stanislav Kovačič. (2005). Symmetric image registration. Medical Image Analysis. 10(3). 484–493. 71 indexed citations
15.
Rogelj, Peter & Stanislav Kovačič. (2004). Spatial deformation models for non-rigid image registration. General and Comparative Endocrinology. 301. 113659–113659. 3 indexed citations
16.
Hasegawa, Ichiro, Hidemasa Uematsu, James C. Gee, et al.. (2003). Voxelwise mapping of magnetic resonance ventilation-perfusion ratio in a porcine model by multimodality registration: technical note1. Academic Radiology. 10(10). 1091–1096. 4 indexed citations
17.
Rogelj, Peter, Stanislav Kovačič, & James C. Gee. (2003). Point similarity measures for non-rigid registration of multi-modal data. Computer Vision and Image Understanding. 92(1). 112–140. 54 indexed citations
18.
Rogelj, Peter, et al.. (2002). Validation of a Non-rigid Registration Algorithm for Multi-modal Data. 1 indexed citations
19.
Rogelj, Peter & Stanislav Kovačič. (2001). <title>Similarity measures for nonrigid registration</title>. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 4322. 569–578. 5 indexed citations
20.
Rogelj, Peter & Stanislav Kovačič. (2001). Similarity measures for non-rigid registration. 569–578. 10 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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