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Large-scale uterine myoma MRI dataset covering all FIGO types with pixel-level annotations

Authors :
Haixia Pan
Minghuang Chen
Wenpei Bai
Bin Li
Xiaoran Zhao
Meng Zhang
Dongdong Zhang
Yanan Li
Hongqiang Wang
Haotian Geng
Weiya Kong
Cong Yin
Linfeng Han
Jiahua Lan
Tian Zhao
Source :
Scientific Data, Vol 11, Iss 1, Pp 1-9 (2024)
Publication Year :
2024
Publisher :
Nature Portfolio, 2024.

Abstract

Abstract 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.

Subjects

Subjects :
Science

Details

Language :
English
ISSN :
20524463
Volume :
11
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Scientific Data
Publication Type :
Academic Journal
Accession number :
edsdoj.886ea874af914d509d3632d7fff20d27
Document Type :
article
Full Text :
https://doi.org/10.1038/s41597-024-03170-x