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Segmentation of female pelvic cavity in axial T2‐weighted MR images towards the 3D reconstruction
Author(s) -
Ma Zhen,
Jorge Renato Natal M.,
Mascarenhas T.,
Tavares João Manuel R.S.
Publication year - 2012
Publication title -
international journal for numerical methods in biomedical engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.741
H-Index - 63
eISSN - 2040-7947
pISSN - 2040-7939
DOI - 10.1002/cnm.2463
Subject(s) - magnetic resonance imaging , segmentation , pelvic cavity , computer science , pelvic floor , radiology , artificial intelligence , medicine , computer vision , anatomy
SUMMARY The anatomies of pelvic structures are critical for the diagnosis of pelvic floor dysfunctions. However, because of the complex background, the imaging appearances of pelvic organs and muscles are frequently distorted by noise and partial volume effect. Magnetic resonance imaging with its clear imaging quality of the female pelvic cavity is preferred for many studies. As such, correct segmentations of the pelvic structures on MR images are required for accurate diagnoses. Effective algorithms for axial T2‐weighted MR images have been proposed, which are based on the imaging features of different structures and various image clues. In this paper, we review these algorithms and evaluate their performance, and discuss implementation issues and aspects towards constructing the three‐dimensional models. Copyright © 2012 John Wiley & Sons, Ltd.