Pan Haixia, Chen Minghuang, Bai Wenpei, Li Bin, Zhao Xiaoran, Zhang Meng, Zhang Dongdong, Li Yanan, Wang Hongqiang, Geng Haotian, Kong Weiya, Yin Cong, Han Linfeng, Lan Jiahua, Zhao Tian
College of Software, Beihang University, Beijing, 100191, China.
Department of Obstetrics and Gynecology, Beijing Shijitan Hospital, Capital Medical University, Beijing, 100038, China.
Sci Data. 2024 Apr 22;11(1):410. doi: 10.1038/s41597-024-03170-x.
Uterine myomas are the most common pelvic tumors in women, which can lead to abnormal uterine bleeding, abdominal pain, pelvic compression symptoms, infertility, or adverse pregnancy. In this article, we provide a dataset named uterine myoma MRI dataset (UMD), which can be used for clinical research on uterine myoma imaging. The UMD is the largest publicly available uterine MRI dataset to date including 300 cases of uterine myoma T2-weighted imaging (T2WI) sagittal patient images and their corresponding annotation files. The UMD covers 9 types of uterine myomas classified by the International Federation of Obstetrics and Gynecology (FIGO), which were annotated and reviewed by 11 experienced doctors to ensure the authority of the annotated data. The UMD is helpful for uterine myomas classification and uterine 3D reconstruction tasks, which has important implications for clinical research on uterine myomas.
子宫肌瘤是女性最常见的盆腔肿瘤，可导致子宫异常出血、腹痛、盆腔压迫症状、不孕或不良妊娠。在本文中，我们提供了一个名为子宫肌瘤MRI数据集（UMD）的数据集，可用于子宫肌瘤成像的临床研究。UMD是迄今为止最大的公开可用子宫MRI数据集，包括300例子宫肌瘤T2加权成像（T2WI）矢状位患者图像及其相应的注释文件。UMD涵盖了国际妇产科联合会（FIGO）分类的9种子宫肌瘤类型，由11位经验丰富的医生进行注释和审核，以确保注释数据的权威性。UMD有助于子宫肌瘤分类和子宫三维重建任务，对子宫肌瘤的临床研究具有重要意义。
