发布首个妇科腹腔镜子宫内膜异位症图像数据集，助力医疗影像智能分析
GLENDA: Gynecologic Laparoscopy Endometriosis Dataset
- 构建基于区域标注的妇科腹腔镜图像数据集
- 包含由专家标注的子宫内膜异位症病灶图像，首份此类公开数据集
- 适用于医学影像分析、手术辅助系统开发的研究者
妇科腹腔镜作为一种微创手术（MIS），通过实时视频流观察患者腹腔内器械插入与操作以实施治疗。该手术不仅支持多种治疗方式，其视频记录也对术后治疗规划、病例存档和医学教育至关重要。然而，当前依赖人工分析手术视频的过程极为耗时。为改善这一状况，计算机视觉与机器学习方法正被积极研发。由于这些方法高度依赖数据，尤其在医疗领域样本稀缺，本文发布首个同类数据集——妇科腹腔镜子宫内膜异位症数据集（GLENDA），包含由领域专家合作标注的子宫内膜异位症病灶图像，旨在推动相关智能分析研究。
原文摘要 · Abstract (English)
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.
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