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Proceedings Paper

Multiwavelet-based feature extraction for MRI segmentation
Author(s): Reza Nezafat; Hamid Soltanian-Zadeh
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Paper Abstract

In this paper, a new feature extraction technique, which is based on multiwavelet frame, is introduced and its application to MRI feature extraction is investigated. Energy calculation is used as the nonlinearity of the feature extraction procedure. An optimal linear transformation is applied to the resulting features to map them onto a 3D subspace in which normal tissues are orthonormal. For brain images, this subspace corresponds to three images which illustrate projections (similarities) of abnormal tissues to each of the normal tissues of the human brain (white matter, gray matter, CSF). The three images, referred to as eigenimages, are useful in diagnosis and treatment of patients with brain abnormalities. We show that the proposed feature extraction method extracts certain brain tumor texture features, which are otherwise invisible. The method is therefore expected to enhance image analysis of MRI studies of brain tumor patients.

Paper Details

Date Published: 19 October 1998
PDF: 10 pages
Proc. SPIE 3458, Wavelet Applications in Signal and Imaging Processing VI, (19 October 1998); doi: 10.1117/12.328136
Show Author Affiliations
Reza Nezafat, Univ. of Tehran (United States)
Hamid Soltanian-Zadeh, Univ. of Tehran (Iran) and Henry Ford Health System (United States)

Published in SPIE Proceedings Vol. 3458:
Wavelet Applications in Signal and Imaging Processing VI
Andrew F. Laine; Michael A. Unser; Akram Aldroubi, Editor(s)

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