Please use this identifier to cite or link to this item: https://hdl.handle.net/10216/54032
Author(s): Zhen Ma
Renato Natal M. Jorge
T. Mascarenhas
João Manuel R. S. Tavares
Title: Segmentation of magnetic resonance images from female pelvic cavity
Issue Date: 2011
Abstract: 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.
Subject: Engenharia mecânica
Mechanical engineering
Scientific areas: Ciências da engenharia e tecnologias::Engenharia mecânica
Engineering and technology::Mechanical engineering
URI: https://repositorio-aberto.up.pt/handle/10216/54032
Source: CompBioMed - 2nd International Conference on Computational & Mathematical Biomedical Engineering
Document Type: Artigo em Livro de Atas de Conferência Internacional
Rights: restrictedAccess
License: https://creativecommons.org/licenses/by-nc/4.0/
Appears in Collections:FEUP - Artigo em Livro de Atas de Conferência Internacional

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