The JNU-IFM dataset for segmenting pubic symphysis-fetal head.

Angle of progression Fetal head Intrapartum transperineal ultrasound Pubic symphysis

Journal

Data in brief
ISSN: 2352-3409
Titre abrégé: Data Brief
Pays: Netherlands
ID NLM: 101654995

Informations de publication

Date de publication:
Apr 2022
Historique:
received: 27 10 2021
revised: 21 01 2022
accepted: 27 01 2022
entrez: 24 2 2022
pubmed: 25 2 2022
medline: 25 2 2022
Statut: epublish

Résumé

The use of transperineal ultrasound techniques for the assessment of fetal head descent and progression is an adjunct to clinical examination. Automatic identification of parameters based on ultrasound images will greatly reduce the subjectivity and non-repeatability of the clinician's judgment. However, the lack of a pubic symphysis-fetal head dataset hinders the development of algorithms. Here, we present an intrapartum transperineal ultrasound dataset of the Intelligent Fetal Monitoring Lab of Jinan University (named the JNU-IFM dataset), in which intrapartum transperineal ultrasound videos of 78 were recorded from 51 patients. These data were obtained with the Youkey D8 wireless 2D ultrasound probe with its corresponding supporting software by Wuhan Youkey Bio-Medical Electronics Co., Ltd., Wuhan, China. In these videos, 6224 high-quality images with four categories were selected to form the JNU- IFM dataset. These images were labelled using the Pair software and then validated by two experienced radiologists. We hope that this data set can be used in the segmentation of the pubic symphysis-fetal head.

Identifiants

pubmed: 35198683
doi: 10.1016/j.dib.2022.107904
pii: S2352-3409(22)00116-0
pmc: PMC8842023
doi:

Banques de données

figshare
['10.6084/m9.figshare.14371652']

Types de publication

Journal Article

Langues

eng

Pagination

107904

Commentaires et corrections

Type : ErratumIn

Informations de copyright

© 2022 The Author(s). Published by Elsevier Inc.

Déclaration de conflit d'intérêts

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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Auteurs

Yaosheng Lu (Y)

College of Information Science and Technology, Jinan University, Guangzhou 510632, China.

Mengqiang Zhou (M)

College of Information Science and Technology, Jinan University, Guangzhou 510632, China.

Dengjiang Zhi (D)

College of Information Science and Technology, Jinan University, Guangzhou 510632, China.

Minghong Zhou (M)

College of Information Science and Technology, Jinan University, Guangzhou 510632, China.

Xiaosong Jiang (X)

College of Information Science and Technology, Jinan University, Guangzhou 510632, China.

Ruiyu Qiu (R)

College of Information Science and Technology, Jinan University, Guangzhou 510632, China.

Zhanhong Ou (Z)

College of Information Science and Technology, Jinan University, Guangzhou 510632, China.

Huijin Wang (H)

College of Information Science and Technology, Jinan University, Guangzhou 510632, China.

Di Qiu (D)

The First Affiliated Hospital of Jinan University, Guangzhou 510632, China.

Mei Zhong (M)

NanFang Hospital of Southern Medical University, Guangzhou 510515, China.

Xiaoxing Lu (X)

Lian-Med Technology Co., Ltd, Guangzhou 510000, China.

Gaowen Chen (G)

Obstetrics and Gynecology Center, Zhujiang Hospital, Southern Medical University, Guangzhou 510260, China.

Jieyun Bai (J)

College of Information Science and Technology, Jinan University, Guangzhou 510632, China.

Classifications MeSH