Dejan Tomaževič

2.0k total citations · 1 hit paper
42 papers, 1.5k citations indexed

About

Dejan Tomaževič is a scholar working on Computer Vision and Pattern Recognition, Biomedical Engineering and Industrial and Manufacturing Engineering. According to data from OpenAlex, Dejan Tomaževič has authored 42 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Computer Vision and Pattern Recognition, 15 papers in Biomedical Engineering and 15 papers in Industrial and Manufacturing Engineering. Recurrent topics in Dejan Tomaževič's work include Industrial Vision Systems and Defect Detection (15 papers), Medical Imaging and Analysis (14 papers) and Medical Imaging Techniques and Applications (12 papers). Dejan Tomaževič is often cited by papers focused on Industrial Vision Systems and Defect Detection (15 papers), Medical Imaging and Analysis (14 papers) and Medical Imaging Techniques and Applications (12 papers). Dejan Tomaževič collaborates with scholars based in Slovenia, Germany and Netherlands. Dejan Tomaževič's co-authors include B. Likar, F. Pernuš, Primož Markelj, Boštjan Likar, Franjo Pernuš, Graeme Penney, Everine B. van de Kraats, Theo van Walsum, T. Slivnik and Wiro J. Niessen and has published in prestigious journals such as PLoS ONE, International Journal of Radiation Oncology*Biology*Physics and Optics Express.

In The Last Decade

Dejan Tomaževič

42 papers receiving 1.4k citations

Hit Papers

A review of 3D/2D registration methods for image-guided i... 2010 2026 2015 2020 2010 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Dejan Tomaževič Slovenia 16 752 537 479 216 169 42 1.5k
Jingfan Fan China 19 833 1.1× 365 0.7× 605 1.3× 177 0.8× 111 0.7× 124 1.5k
Shun Miao United States 16 524 0.7× 416 0.8× 456 1.0× 182 0.8× 109 0.6× 41 1.2k
Toby Collins France 21 682 0.9× 312 0.6× 216 0.5× 331 1.5× 376 2.2× 64 1.2k
Yazhu Chen China 17 310 0.4× 292 0.5× 299 0.6× 89 0.4× 102 0.6× 99 982
Manning Wang China 22 645 0.9× 302 0.6× 378 0.8× 175 0.8× 331 2.0× 124 1.7k
Alexandre Krupa France 16 395 0.5× 568 1.1× 137 0.3× 236 1.1× 185 1.1× 49 905
F. Pernuš Slovenia 13 813 1.1× 511 1.0× 584 1.2× 213 1.0× 160 0.9× 31 1.5k
R. James Housden United Kingdom 22 230 0.3× 652 1.2× 579 1.2× 197 0.9× 69 0.4× 76 1.4k
Jong Beom South Korea 17 747 1.0× 287 0.5× 336 0.7× 72 0.3× 117 0.7× 124 1.2k
Floris Ernst Germany 21 317 0.4× 462 0.9× 415 0.9× 256 1.2× 98 0.6× 118 1.3k

Countries citing papers authored by Dejan Tomaževič

Since Specialization
Citations

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

Fields of papers citing papers by Dejan Tomaževič

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dejan Tomaževič

This figure shows the co-authorship network connecting the top 25 collaborators of Dejan Tomaževič. A scholar is included among the top collaborators of Dejan Tomaževič 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 Dejan Tomaževič. Dejan Tomaževič 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.
Tomaževič, Dejan, et al.. (2024). Coupling of unsupervised and supervised deep learning-based approaches for surface anomaly detection. Journal of Electronic Imaging. 33(3). 1 indexed citations
2.
Šibanc, Rok, et al.. (2022). 100% visual inspection of tablets produced with continuous direct compression and coating. International Journal of Pharmaceutics. 614. 121465–121465. 11 indexed citations
3.
Likar, Boštjan, et al.. (2018). In-line agglomeration degree estimation in fluidized bed pellet coating processes using visual imaging. International Journal of Pharmaceutics. 546(1-2). 78–85. 19 indexed citations
4.
Lavrič, Zoran, et al.. (2018). In-Line Film Coating Thickness Estimation of Minitablets in a Fluid-Bed Coating Equipment. AAPS PharmSciTech. 19(8). 3440–3453. 7 indexed citations
5.
Pernuš, Franjo, et al.. (2014). Real-Time Rotation Estimation Using Histograms of Oriented Gradients. PLoS ONE. 9(3). e92137–e92137. 5 indexed citations
6.
Šibanc, Rok, et al.. (2014). In-line monitoring of pellet coating thickness growth by means of visual imaging. International Journal of Pharmaceutics. 470(1-2). 8–14. 31 indexed citations
7.
Bürmen, Miran, et al.. (2013). Characterization of a spectrograph based hyperspectral imaging system. Optics Express. 21(10). 12085–12085. 15 indexed citations
8.
Tomaževič, Dejan, et al.. (2010). Digital imaging as a process analytical technology tool for fluid-bed pellet coating process. European Journal of Pharmaceutical Sciences. 41(1). 156–162. 40 indexed citations
9.
Markelj, Primož, Dejan Tomaževič, B. Likar, & F. Pernuš. (2010). A review of 3D/2D registration methods for image-guided interventions. Medical Image Analysis. 16(3). 642–661. 520 indexed citations breakdown →
10.
Bürmen, Miran, et al.. (2009). Automatic visual inspection of pharmaceutical pellets in coating process. 4. 1–5. 4 indexed citations
11.
Markelj, Primož, Dejan Tomaževič, Franjo Pernuš, & Boštjan Likar. (2008). Robust Gradient-Based 3-D/2-D Registration of CT and MR to X-Ray Images. IEEE Transactions on Medical Imaging. 27(12). 1704–1714. 64 indexed citations
12.
Tomaževič, Dejan, et al.. (2006). Evaluation of similarity measures for reconstruction-based registration in image-guided radiotherapy and surgery. International Journal of Radiation Oncology*Biology*Physics. 65(3). 943–953. 16 indexed citations
13.
Tomaževič, Dejan, B. Likar, & F. Pernuš. (2005). 3-D/2-D registration by integrating 2-D information in 3-D. IEEE Transactions on Medical Imaging. 25(1). 17–27. 57 indexed citations
14.
Kraats, Everine B. van de, Graeme Penney, Dejan Tomaževič, Theo van Walsum, & Wiro J. Niessen. (2005). Standardized evaluation methodology for 2-D-3-D registration. IEEE Transactions on Medical Imaging. 24(9). 1177–1189. 155 indexed citations
15.
Tomaževič, Dejan, Boštjan Likar, & Franjo Pernuš. (2004). “Gold standard” data for evaluation and comparison of 3D/2D registration methods. Computer Aided Surgery. 9(4). 137–144. 30 indexed citations
16.
Tomaževič, Dejan, Boštjan Likar, & Franjo Pernuš. (2004). “Gold standard” data for evaluation and comparison of 3D/2D registration methods. Computer Aided Surgery. 9(4). 137–144. 10 indexed citations
17.
Tomaževič, Dejan, B. Likar, T. Slivnik, & F. Pernuš. (2003). 3-D/2-D registration of CT and MR to X-ray images. IEEE Transactions on Medical Imaging. 22(11). 1407–1416. 123 indexed citations
18.
Likar, Boštjan, et al.. (2003). Real-time automated visual inspection of color tablets in pharmaceutical blisters. Real-Time Imaging. 9(2). 113–124. 36 indexed citations
19.
Tomaževič, Dejan, B. Likar, & F. Pernuš. (2002). A comparison of retrospective shading correction techniques. 3. 564–567. 6 indexed citations
20.
Tomaževič, Dejan, B. Likar, & F. Pernuš. (2002). Comparative evaluation of retrospective shading correction methods. Journal of Microscopy. 208(3). 212–223. 71 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026