Multiwavelet-based feature extraction for MRI segmentation

Reza Nezafat; Hamid Soltanian-Zadeh

doi:10.1117/12.328136

19 October 1998 Multiwavelet-based feature extraction for MRI segmentation

Reza Nezafat, Hamid Soltanian-Zadeh

Proceedings Volume 3458, Wavelet Applications in Signal and Imaging Processing VI; (1998) https://doi.org/10.1117/12.328136
Event: SPIE's International Symposium on Optical Science, Engineering, and Instrumentation, 1998, San Diego, CA, United States

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.

Citation Download Citation

Reza Nezafat and Hamid Soltanian-Zadeh "Multiwavelet-based feature extraction for MRI segmentation", Proc. SPIE 3458, Wavelet Applications in Signal and Imaging Processing VI, (19 October 1998); https://doi.org/10.1117/12.328136

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