ICA for Ovary Tissue Classification of Perfusion Magnetic Resonance Images

Author

Rieta, J.J. ; Moratal, D. ; Marti-Bonmati, L. ; Molina-Minguez, R. ; Valles-Lluch, A. ; Sanz, R.

Author_Institution

Valencia Univ. of Technol., Gandia

fYear

2007

fDate

22-26 Aug. 2007

Firstpage

1611

Lastpage

1614

Abstract

In this study, a method to segment ovary magnetic resonance (MR) images and distinguish healthy tissue from cysts has been described. Through the application of independent component analysis (ICA) to a set of perfusion MR images it was possible to extract the output independent components and their corresponding signal-time curves. After examining and analyzing this result, a polynomial approach was computed to represent the main features of each curve, and automated particular selection of independent components was obtained by applying a Bayesian information criterion able to show the most relevant components. The results shown in this work permit to conclude that the independent components with a step-like signal-time curve allow to distinguish healthy tissue from cysts, thus, giving very promising results for the application of ICA to ovary tissue segmentation of perfusion MR images.

Keywords

Bayes methods; biological tissues; biomedical MRI; haemorheology; image classification; image segmentation; independent component analysis; medical image processing; polynomials; Bayesian information; ICA; independent component analysis; magnetic resonance images; ovary tissue classification; perfusion; polynomial approach; tissue segmentation; Biological materials; Biomedical imaging; Image analysis; Image segmentation; Independent component analysis; Magnetic analysis; Magnetic resonance; Magnetic resonance imaging; Source separation; Vectors; Algorithms; Artificial Intelligence; Female; Humans; Image Enhancement; Image Interpretation, Computer-Assisted; Magnetic Resonance Imaging; Ovarian Cysts; Ovary; Pattern Recognition, Automated; Principal Component Analysis; Reproducibility of Results; Sensitivity and Specificity;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE

Conference_Location

Lyon

ISSN

1557-170X

Print_ISBN

978-1-4244-0787-3

Type

conf

DOI

10.1109/IEMBS.2007.4352614

Filename

4352614