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GLENDA: Gynecologic Laparoscopy Endometriosis Dataset

机译：GLENDA：妇科腹腔镜子宫内膜异位症数据集

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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 field 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 first of its kind and it has been created in collaboration with leading medical experts in the field.
机译：妇科腹腔镜检查是一种微创外科手术（MIS），是通过对患者腹部的活体进食进行的，以实地调查各种进行治疗的器械的插入和操作情况来进行的。采用这种外科手术不仅可以促进多种治疗，而且记录所述视频流的可能性对于许多外科手术后活动也很重要，例如治疗计划，病例记录和教育。然而，如在当前实践中所进行的那样，手动分析手术记录的过程通常被证明是费时的。为了改善这种情况，积极开发了更复杂的计算机视觉以及机器学习方法。由于大多数此类方法都严重依赖于样本数据，尤其是在医学领域，这种数据很少获得，因此我们发布了妇科腹腔镜子宫内膜异位症DAtaset（GLENDA）-一种图像数据集，其中包含基于区域的常见医学病状注释，子宫内膜异位，即子宫样组织脱位。该数据集是同类数据库中的第一个，它是与该领域的领先医学专家合作创建的。

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