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Wavelet Transform in Biomedical Image Segmentation and Classification

Publication at Second Faculty of Medicine |
2011

Abstract

The contribution is devoted to the study of image segmentation and texture analysis to find image features invariant to image components rotation and translation. The main part of the paper presents the principle of Radon transform and its use in combination with the wavelet transform to find features minimizing their variance due to image components rotation.

Proposed methods have been verified for simulated structures and then used for analysis of biomedical images including magnetic resonance images of the brain and orthodontic images. The goal of image processing included in all cases (i) segmentation of selected biomedical objects and (ii) detection of their features.