Go to:
Logótipo
Comuta visibilidade da coluna esquerda
Você está em: Start > Publications > View > Segmentation of magnetic resonance images from female pelvic cavity
Publication

Publications

Segmentation of magnetic resonance images from female pelvic cavity

Title
Segmentation of magnetic resonance images from female pelvic cavity
Type
Article in International Conference Proceedings Book
Year
2011
Authors
Zhen Ma
(Author)
FEUP
View Personal Page You do not have permissions to view the institutional email. Search for Participant Publications Without AUTHENTICUS Without ORCID
Renato Natal M. Jorge
(Author)
FEUP
View Personal Page You do not have permissions to view the institutional email. Search for Participant Publications View Authenticus page View ORCID page
T. Mascarenhas
(Author)
Other
The person does not belong to the institution. The person does not belong to the institution. The person does not belong to the institution. Without AUTHENTICUS Without ORCID
João Manuel R. S. Tavares
(Author)
FEUP
View Personal Page You do not have permissions to view the institutional email. Search for Participant Publications View Authenticus page View ORCID page
Conference proceedings International
Pages: 305-308
CompBioMed - 2nd International Conference on Computational & Mathematical Biomedical Engineering Washington D.C., USA 30th March - 1st April 2011 ISBN: 978-0-9562914-1-7
Washington D.C., USA, 30th March - 1st April 2011
Scientific classification
FOS: Engineering and technology > Mechanical engineering
Other information
Abstract (EN): Magnetic resonance imaging is currently one imaging modality for studying pelvic floor dysfunctions. In order to perform biomechanical analysis, the geometrical models of the concerned structures are needed, which implies that these structures should be segmented in the acquired image series. However, the appearances of the organs and muscles of female pelvic cavity can be easily distorted in the images by noise and partial volume effect, which leads to the failure of common segmentation algorithms. In this study, we propose algorithms to handle the segmentations of the pelvic organs and muscles in T2-weighted axial magnetic resonance images. The proposed algorithms are based on the imaging features of different structures, and use various image clues and prior knowledge for the segmentation. Implementation details and further issues are introduced and discussed. Additionally, numerical examples are included to demonstrate the effectiveness of the proposed algorithms.
Language: English
Type (Professor's evaluation): Scientific
Contact: www.fe.up.pt/~tavares
No. of pages: 4
License type: Click to view license CC BY-NC
Documents
We could not find any documents associated to the publication with allowed access.
Recommend this page Top
Copyright 1996-2025 © Faculdade de Direito da Universidade do Porto  I Terms and Conditions  I Acessibility  I Index A-Z
Page created on: 2025-07-10 at 08:49:52 | Privacy Policy | Personal Data Protection Policy | Whistleblowing