Automated Author ProfileBrawura Biskupski Samaha, Robert
0000-0001-5784-873x
Brawura Biskupski Samaha, Robert
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 3.8 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
This is the dataset related to the paper:Płotka, Szymon, et al. "Real-time placental vessel segmentation in fetoscopic laser surgery for Twin-to-Twin Transfusion Syndrome." Medical Image Analysis 99 (2025): 103330. We release the TTTSNet dataset, a fetoscopic video dataset consisting of 4,408 frames (2,060 for training and validation, and 2,348 for testing), obtained from 42 independent patients who underwent TTTS fetoscopic procedures at six European fetal surgery centers. Data from centers A and B are publicly available, while data from centers C, D, E, and F are newly released to the community to foster research in this domain. Please note: The FetReg2021 dataset (from Centers A and B), which is currently publicly accessible, contains pixel-wise annotations that omit small placental vessel segmentation and include incomplete labels for larger vessels. For the purposes of this paper, these segmentations were revised to align with our segmentation protocol. If you use this dataset, please cite our research:@article{plotka2025real, title={Real-time placental vessel segmentation in fetoscopic laser surgery for Twin-to-Twin Transfusion Syndrome}, author={P{\l}otka, Szymon and Szczepa{'n}ski, Tomasz and Szenejko, Paula and Korzeniowski, Przemys{\l}aw and Calvo, Jes{'u}s Rodriguez and Khalil, Asma and Shamshirsaz, Alireza and Brawura-Biskupski-Samaha, Robert and I{\v{s}}gum, Ivana and S{'a}nchez, Clara I and others}, journal={Medical Image Analysis}, volume={99}, pages={103330}, year={2025}, publisher={Elsevier}}
Authors
- Płotka, Szymon ;
- Szczepański, Tomasz ;
- Szenejko, Paula Idalia ;
- Brawura Biskupski Samaha, Robert ;
- Khalil, Asma ;
- Rodriguez Calvo, Jesús ;
- Shamshirsaz, Alireza ;
- Isgum, Ivana ;
- Sánchez Gutiérrez, Clara Isabel ;
- Sitek, Arkadiusz
This is the dataset related to the paper:Płotka, Szymon, et al. "Real-time placental vessel segmentation in fetoscopic laser surgery for Twin-to-Twin Transfusion Syndrome." Medical Image Analysis 99 (2025): 103330. We release the TTTSNet dataset, a fetoscopic video dataset consisting of 4,408 frames (2,060 for training and validation, and 2,348 for testing), obtained from 42 independent patients who underwent TTTS fetoscopic procedures at six European fetal surgery centers. Data from centers A and B are publicly available, while data from centers C, D, E, and F are newly released to the community to foster research in this domain. Please note: The FetReg2021 dataset (from Centers A and B), which is currently publicly accessible, contains pixel-wise annotations that omit small placental vessel segmentation and include incomplete labels for larger vessels. For the purposes of this paper, these segmentations were revised to align with our segmentation protocol. If you use this dataset, please cite our research:@article{plotka2025real, title={Real-time placental vessel segmentation in fetoscopic laser surgery for Twin-to-Twin Transfusion Syndrome}, author={P{\l}otka, Szymon and Szczepa{'n}ski, Tomasz and Szenejko, Paula and Korzeniowski, Przemys{\l}aw and Calvo, Jes{'u}s Rodriguez and Khalil, Asma and Shamshirsaz, Alireza and Brawura-Biskupski-Samaha, Robert and I{\v{s}}gum, Ivana and S{'a}nchez, Clara I and others}, journal={Medical Image Analysis}, volume={99}, pages={103330}, year={2025}, publisher={Elsevier}}
Authors
- Płotka, Szymon ;
- Szczepański, Tomasz ;
- Szenejko, Paula Idalia ;
- Brawura Biskupski Samaha, Robert ;
- Khalil, Asma ;
- Rodriguez Calvo, Jesús ;
- Shamshirsaz, Alireza ;
- Isgum, Ivana ;
- Sánchez Gutiérrez, Clara Isabel ;
- Sitek, Arkadiusz