Content-Based Retrieval of Biomedical Images Using Orthogonal Fourier-Mellin Moments

Abstract

Biomedical imaging field is growing enormously from last decade. The medical images have been used and stored continuously for diagnosis as well as research purposes. For real-time retrieval of medical images from such storage repositories there is a grave need of an effective and efficient biomedical image indexing and retrieval approach. In this quest, this thesis work presents a new approach for the retrieval of CT and MR images using orthogonal Fourier-Mellin moments (OFMMs). OFMMs have excellent information representation capability that enables them to pack the entire image information in very less number of coefficients. This property makes the proposed approach not only effective but also computationally very efficient and most favourable among all the existing approaches. The proposed approach has been tested and compared with numerous existing, state-of-the-art as well as recently published biomedical indexing and retrieval approaches on four standard databases namely, Emphysema CT, NEMA CT, OASIS MRI and NEMA MRI. Additional experiments have been conducted to analyse the noise robustness ability of the proposed and all the compared approaches. The reported results show a significant increase in the retrieval rate of the proposed approach over all the existing approaches on noise free Emphysema CT and OASIS MRI medical databases and noisy images of all the test medical databases.