  Hysteroscopy enables direct visualization of morphological changes in the
endometrium, serving as an important means for screening, diagnosing, and
treating intrauterine lesions. Accurate identification of the benign or
malignant nature of diseases is crucial. However, the complexity and
variability of uterine morphology increase the difficulty of identification,
leading to missed diagnoses and misdiagnoses, often requiring the expertise of
experienced gynecologists and pathologists. Here, we provide the video and
image dataset of hysteroscopic examinations conducted at Beijing Chaoyang
Hospital, Capital Medical University (named the HS-CMU dataset), recording
videos of 175 patients undergoing hysteroscopic surgery to explore the uterine
cavity. These data were obtained using corresponding supporting software. From
these videos, 3385 high-quality images from 8 categories were selected to form
the HS-CMU dataset. These images were annotated by two experienced
obstetricians and gynecologists using lableme software. We hope that this
dataset can be used as an auxiliary tool for the diagnosis of intrauterine
benign and malignant diseases.
