The BAGLS dataset
We provide here a benchmark dataset for glottis segmentation (BAGLS). It features the following specifications:
- 55750 training images and their corresponding segmentation
- 3500 test images and their corresponding segmentation
If you are interested in the dataset, please write to Prof. Dr. Michael Döllinger.
Benchmark for Automatic Glottis Segmentation (BAGLS)
Website of the Benchmark for Automatic Glottis Segmentation (BAGLS)
BAGLS and BAGLS-RT Data Sets
available at:
Benchmark for Automatic Glottis Segmentation (BAGLS)
Re-Training Extension of the Benchmark for Automatic Glottis Segmentation (BAGLS-RT)
Contact Person
Staff
Publications
P. Gomez, A. M. Kist, P. Schlegel, D. A. Berry, D. K. Chhetri, S. Dürr, M. Echternach, A. M. Johnson, S. Kniesburges, M. Kunduk, Y. Maryn, A. Schützenberger, M. Verguts, M. Döllinger. BAGLS, a multihospital benchmark for automatic glottis segmentation. Scientific Data, 7(1):186; 2020.
M. Döllinger, T. Schraut, L.A. Henrich, D. Chhetri, M. Echternach, A.M. Johnson, M. Kunduk, Y. Maryn, R.R. Patel, R. Samlan, M. Semmler, A. Schützenberger. Re-training of convolutional neural networks for glottis segmentation in endoscopic high-speed videos. Appl. Sci., 12, 9791, 2022. https://doi.org/10.3390/app12199791
