Nataša Sladoje
- Computer Vision and Pattern Recognition top 5%
- Media Technology top 5%
- Biophysics top 5%
- Artificial Intelligence
- Radiology, Nuclear Medicine and Imaging
- Co-authors
- Joakim LindbladIngela NyströmKota MiuraPunam K. SahaFilip MalmbergStefan G. StanciuIda‐Maria SintornAttila Tanács
- Topics
- Medical Image Segmentation Techniques (21 papers)Image and Object Detection Techniques (11 papers)AI in cancer detection (10 papers)
In The Last Decade
Nataša Sladoje
52 papers receiving 400 citations
Peers
Comparison fields: 5 of 112
- Computer Vision and Pattern Recognition 220
- Media Technology 64
- Biophysics 61
- Artificial Intelligence 54
- Radiology, Nuclear Medicine and Imaging 37
Countries citing papers authored by Nataša Sladoje
This map shows the geographic impact of Nataša Sladoje'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 Nataša Sladoje with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nataša Sladoje more than expected).
Fields of papers citing papers by Nataša Sladoje
This network shows the impact of papers produced by Nataša Sladoje. 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 Nataša Sladoje. The network helps show where Nataša Sladoje may publish in the future.
Co-authorship network of co-authors of Nataša Sladoje
This figure shows the co-authorship network connecting the top 25 collaborators of Nataša Sladoje. A scholar is included among the top collaborators of Nataša Sladoje 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 Nataša Sladoje. Nataša Sladoje is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 2 | |
| 3 | 4 | |
| 4 | 3 | |
| 5 | 1 | |
| 6 | 2 | |
| 7 | 15 | |
| 8 | 4 | |
| 9 | 13 | |
| 10 | 21 | |
| 11 | CoMIR: Contrastive Multimodal Image Representation for Registration | 2 |
| 12 | 5 | |
| 13 | 17 | |
| 14 | 52 | |
| 15 | 2 | |
| 16 | The Coverage Model and Its Use in Image Processing | 4 |
| 17 | Precise estimation of the projection of a shape from a pixel coverage representation | 2 |
| 18 | 5 | |
| 19 | 25 | |
| 20 | 30 |
About Nataša Sladoje
Nataša Sladoje is a scholar working on Computer Vision and Pattern Recognition, Biophysics and Media Technology, having authored 52 papers that have together received 407 indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (21 papers), Image and Object Detection Techniques (11 papers) and AI in cancer detection (10 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (220 citations), Biophysics (61 citations) and Media Technology (64 citations). Nataša Sladoje has collaborated with scholars based in Sweden, Serbia and Romania. Frequent co-authors include Joakim Lindblad, Ingela Nyström, Kota Miura, Punam K. Saha, Filip Malmberg, Stefan G. Stanciu, Ida‐Maria Sintorn, Attila Tanács, Zoltán Kató and Mariana Costache. Their work appears in journals such as PLoS ONE, IEEE Transactions on Pattern Analysis and Machine Intelligence and Scientific Reports.
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.