GLENDA: Gynecologic Laparoscopy Endometriosis Dataset

Gynecologic laparoscopy as a type of minimally invasive surgery

(MIS) is performed via a live feed of a patient's abdomen surveying

the insertion and handling of various instruments for conducting

treatment. Adopting this kind of surgical intervention not only facilitates

a great variety of treatments, the possibility of recording said video

streams is as well essential for numerous post-surgical activities, such

as treatment planning, case documentation and education. Nonetheless,

the process of manually analyzing surgical recordings, as it is carried out

in current practice, usually proves tediously time-consuming. In order

to improve upon this situation, more sophisticated computer vision as

well as machine learning approaches are actively developed. Since most

of such approaches heavily rely on sample data, which especially in the

medical eld is only sparsely available, with this work we publish the

Gynecologic Laparoscopy ENdometriosis DAtaset (GLENDA) { an image

dataset containing region-based annotations of a common medical

condition named endometriosis, i.e. the dislocation of uterine-like tissue.

The dataset is the rst of its kind and it has been created in collaboration

with leading medical experts in the eld.