Deep learning models for segmentation of dynamic axial MRI of hernia patients

DOI

This dataset contains anonymized axial magnetic resonance imaging (MRI) data of abdominal region of eighteen in vivo participants having an abdominal hernia. The acquisitions were made both before and after their hernia surgery, performing three exercises: breathing, coughing and Valsalva. This dataset includes the pre-processed anatomical MRI slices and corresponding ground truth segmented masks. Please look at the README file for more informations

Python, 3.9

Identifier
DOI https://doi.org/10.57745/HDJYZ8
Related Identifier IsCitedBy https://doi.org/10.1007/s10029-025-03337-4
Related Identifier IsCitedBy https://openreview.net/pdf?id=fZoD19wN20
Metadata Access https://entrepot.recherche.data.gouv.fr/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.57745/HDJYZ8
Provenance
Creator Belton, Niamh ORCID logo; Joppin, Victoria ORCID logo; Lawlor, Aonghus ORCID logo; Curran, Kathleen ORCID logo; Bège, Thierry ORCID logo; Masson, Catherine ORCID logo; Bendahan, David ORCID logo
Publisher Recherche Data Gouv
Contributor Masson, Catherine; Belton, Niamh; Joppin, Victoria; University College Dublin; Université Gustave Eiffel; Entrepôt-Catalogue Recherche Data Gouv
Publication Year 2026
Rights info:eu-repo/semantics/restrictedAccess
OpenAccess false
Contact Masson, Catherine (LBA ; Université Gustave Eiffel); Belton, Niamh (University College of Dublin); Joppin, Victoria (LBA ; Université Gustave Eiffel)
Representation
Resource Type Dataset
Format application/zip; application/pdf
Size 40941117; 9215814319; 579348
Version 1.0
Discipline Life Sciences; Medicine