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Identification of body fat tissues in MRI data

Ilea, Dana E. and Ghita, Ovidiu and Robinson, Kevin and Sadleir, Robert and Lynch, Michael and Brennan, Darren and Whelan, Paul F. (2004) Identification of body fat tissues in MRI data. In: OPTIM 2004 - 9th International Conference on Optimization of Electrical and Electronic Equipment, 20-21 May 2004, Brasov, Romania.

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Abstract

In recent years non-invasive medical diagnostic techniques have been used widely in medical investigations. Among the various imaging modalities available, Magnetic Resonance Imaging is very attractive as it produces multi-slice images where the contrast between various types of body tissues such as muscle, ligaments and fat is well defined. The aim of this paper is to describe the implementation of an unsupervised image analysis algorithm able to identify the body fat tissues from a sequence of MR images encoded in DICOM format. The developed algorithm consists of three main steps. The first step pre-processes the MR images in order to reduce the level of noise. The second step extracts the image areas representing fat tissues by using an unsupervised clustering algorithm. Finally, image refinements are applied to reclassify the pixels adjacent to the initial fat estimate and to eliminate outliers. The experimental data indicates that the proposed implementation returns accurate results and furthermore is robust to noise and to greyscale in-homogeneity.

Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Uncontrolled Keywords:MRI; body fat; image de-noising; image segmentation; clustering; region growing;
Subjects:Computer Science > Image processing
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Electronic Engineering
Research Initiatives and Centres > Research Institute for Networks and Communications Engineering (RINCE)
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
ID Code:4679
Deposited On:07 Jul 2009 11:52 by DORAS Administrator. Last Modified 07 Jul 2009 11:52

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