Automated Author Profile

Bodenstedt, Sebastian

Current S-Index

2.9

Sum of Dataset Indices for all datasets

Average Dataset Index per Dataset

1.4

Average Dataset Index per dataset

Total Datasets

2

Total datasets for this author

Average FAIR Score

82.7%

Average FAIR Score per dataset

Total Citations

2

Total citations to the author's datasets

Total Mentions

0

Total mentions of the author's datasets

S-Index Interpretation

S-Index Over Time

Cumulative Citations Over Time

Cumulative Mentions Over Time

Datasets

The Dresden Surgical Anatomy Dataset for abdominal organ segmentation in surgical data science

The Dresden Surgical Anatomy Dataset provides semantic segmentations of eight abdominal organs (colon, liver, pancreas, small intestine, spleen, stomach, ureter, vesicular glands), the abdominal wall and two vessel structures (inferior mesenteric artery, intestinal veins) in laparoscopic view. In total, this dataset comprises 13195 laparoscopic images with pixel-wise segmentations as well as categorical annotations of organ presence. The dataset can be used for various purposes in the field of surgical data science including abdominal organ segmentation and computer vision-based intraoperative decision support.

Authors

  • Carstens, Matthias ;
  • Rinner, Franziska ;
  • Bodenstedt, Sebastian ;
  • Jenke, Alexander ;
  • Weitz, Jürgen ;
  • Distler, Marius ;
  • Speidel, Stefanie ;
  • Kolbinger, Fiona
2 Citations0 Mentions81% FAIR2.6 Dataset Index
10.6084/m9.figshare.217026002022

The Dresden Surgical Anatomy Dataset for abdominal organ segmentation in surgical data science

The Dresden Surgical Anatomy Dataset provides semantic segmentations of eight abdominal organs (colon, liver, pancreas, small intestine, spleen, stomach, ureter, vesicular glands), the abdominal wall and two vessel structures (inferior mesenteric artery, intestinal veins) in laparoscopic view. In total, this dataset comprises 13195 laparoscopic images with pixel-wise segmentations as well as categorical annotations of organ presence. The dataset can be used for various purposes in the field of surgical data science including abdominal organ segmentation and computer vision-based intraoperative decision support.

Authors

  • Carstens, Matthias ;
  • Rinner, Franziska ;
  • Bodenstedt, Sebastian ;
  • Jenke, Alexander ;
  • Weitz, Jürgen ;
  • Distler, Marius ;
  • Speidel, Stefanie ;
  • Kolbinger, Fiona
0 Citations0 Mentions85% FAIR0.3 Dataset Index
10.6084/m9.figshare.21702600.v12022