Medical image classification via sparse representations
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Ελευθερία, Κολοκυθά
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Abstract
In this thesis, we study the problem of recognizing/classifying different body
parts from Magnetic Resonance Images (MRI). We follow an approach that
utilizes the compressed sensing/sparse representations theory. Our work is based upon a recently proposed image classification method that utilizes sparse representations for the problem of face recognition. In this thesis, we propose a proper modification of that method that makes it robust against spatial translations (shifts).
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Keywords
Classification, Medical images, Sparse represantation theory