MorphoSeg: An uncertainty-aware deep learning method for biomedical segmentation of complex cellular morphologies

Zhang, T., McCourty, H.J., Sanchez-Tafolla, B.M. et al. (2 more authors) (2025) MorphoSeg: An uncertainty-aware deep learning method for biomedical segmentation of complex cellular morphologies. Neurocomputing, 647. 130511. ISSN 0925-2312

Abstract

Metadata

Item Type: Article
Authors/Creators:
Copyright, Publisher and Additional Information:

© 2025 The Authors. Except as otherwise noted, this author-accepted version of a journal article published in Neurocomputing is made available via the University of Sheffield Research Publications and Copyright Policy under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/

Keywords: Biomedical Segmentation; Cell Segmentation; Machine Learning; Deep Learning; Ntera-2 Cells; Data Repository; Complex Cell Shapes; Vision Transformer
Dates:
  • Submitted: 24 September 2024
  • Accepted: 11 May 2025
  • Published (online): 29 May 2025
  • Published: 28 September 2025
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > School of Electrical and Electronic Engineering
Funding Information:
Funder
Grant number
ENGINEERING AND PHYSICAL SCIENCE RESEARCH COUNCIL
EP/T013265/1
ENGINEERING AND PHYSICAL SCIENCE RESEARCH COUNCIL
EP/V026747/1
Depositing User: Symplectic Sheffield
Date Deposited: 07 May 2025 13:45
Last Modified: 06 Jun 2025 14:56
Status: Published
Publisher: Elsevier
Refereed: Yes
Identification Number: 10.1016/j.neucom.2025.130511
Open Archives Initiative ID (OAI ID):

Export

Statistics