Andrius Ušinskas
- Computer Vision and Pattern Recognition top 10%
- Radiology, Nuclear Medicine and Imaging
- Genetics
- Artificial Intelligence
- Epidemiology
- Co-authors
- Bernd TomandlJurgita UšinskienėVasileios K. KatsarosDarius NorkusKęstutis SužiedėlisSaulius RočkaAgnė UlytėAtle Bjørnerud
- Topics
- Medical Image Segmentation Techniques (11 papers)Brain Tumor Detection and Classification (3 papers)Advanced Image and Video Retrieval Techniques (3 papers)
In The Last Decade
Andrius Ušinskas
17 papers receiving 225 citations
Peers
Comparison fields: 5 of 73
- Computer Vision and Pattern Recognition 104
- Radiology, Nuclear Medicine and Imaging 82
- Genetics 51
- Artificial Intelligence 37
- Epidemiology 36
Countries citing papers authored by Andrius Ušinskas
This map shows the geographic impact of Andrius Ušinskas'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 Andrius Ušinskas with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andrius Ušinskas more than expected).
Fields of papers citing papers by Andrius Ušinskas
This network shows the impact of papers produced by Andrius Ušinskas. 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 Andrius Ušinskas. The network helps show where Andrius Ušinskas may publish in the future.
Co-authorship network of co-authors of Andrius Ušinskas
This figure shows the co-authorship network connecting the top 25 collaborators of Andrius Ušinskas. A scholar is included among the top collaborators of Andrius Ušinskas 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 Andrius Ušinskas. Andrius Ušinskas is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 1 | |
| 6 | 72 | |
| 7 | 0 | |
| 8 | 0 | |
| 9 | 2 | |
| 10 | 7 | |
| 11 | 2 | |
| 12 | 114 | |
| 13 | Dirbtinių intrakranijinės aneurizmos modelių kūrimas angiografiniams tyrimams | 1 |
| 14 | 2 | |
| 15 | 1 | |
| 16 | 4 | |
| 17 | 32 | |
| 18 | 4 | |
| 19 | Segmentation of Ischemic Stroke in CT Images of Human Brain | 0 |
| 20 | 5 |
About Andrius Ušinskas
Andrius Ušinskas is a scholar working on Computer Vision and Pattern Recognition, Geology and Neurology, having authored 20 papers that have together received 251 indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (11 papers), Brain Tumor Detection and Classification (3 papers) and Advanced Image and Video Retrieval Techniques (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (104 citations), Genetics (51 citations) and Radiology, Nuclear Medicine and Imaging (82 citations). Andrius Ušinskas has collaborated with scholars based in Lithuania, Germany and Finland. Frequent co-authors include Bernd Tomandl, Jurgita Ušinskienė, Vasileios K. Katsaros, Darius Norkus, Kęstutis Sužiedėlis, Saulius Ročka, Agnė Ulytė, Atle Bjørnerud, Eduardas Aleknavičius and Darius Miniotas. Their work appears in journals such as Applied Sciences, Electronics and Neuroradiology.
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.