Endometriosis is as well very frequently found on ovaries, the outer capsule of which appears in a shade of white.
Uterine endometriosis or adenomyosis thickens the organ, which typically is colored in a red-tint.
Non-shallow endometriosis that is found on specific locations such as the rectum, the rectovaginal space or uterine ligaments is described as Deep Infil- trating Endometriosis (DIE). Due to the variety of involved locations no distinct visual appearance can be attributed to this type of class, other than highlighting that typically the color spectrum in recorded laparascopic videos lacks green tones.
Video sequences containing no visible pathology in relation to endometriosis are included in the dataset, providing counter examples to above categories. Since this class does not contain any region-based annotations, in addition to a sequence showing a non-pathological uterus, below listing particularly includes examples of several anatomical structures from above pathological classes (e.g. peritoneum and ovaries). Again it is not possible to make any assumptions about the color and shape of objects within this class, since it includes images covering most areas of the pelvic region.
|no pathology||0||0||0||27||13 438|
(max. classes: 3)
*Note: A sequence/keyframe/frame is attributed to a specific category if it is the dominant one in all of its corresponding annotations in terms of annotation count/area covered.
For further information about the dataset's organization see 'Readme.txt' within the download archive below.
The dataset is exclusively provided for scientific research purposes and as such cannot be used commercially or for any other purpose. If any other purpose is intended, you may directly contact the originator of the videos, Prof. Dr. Jörg Keckstein.
In addition, reference must be made to the following publication when this dataset is used in any academic and research reports:
A. Leibetseder, S. Kletz, K. Schoeffmann, S. Keckstein and J. Keckstein. 2020. GLENDA: Gynecologic Laparoscopy Endometriosis Dataset. To appear: In Proceedings of the 26th International Conference on Multimedia Modeling, MMM 2020. Springer, Cham.
GLENDA is licensed under Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0, ) and is created as well as maintained by Distributed Multimedia Systems Group of the Institute of Information Technology (ITEC) at Alpen-Adria Universität in Klagenfurt, Austria.
This license allows users of this dataset to copy, distribute and transmit the work under the following conditions: