A new approach for effective retrieval and indexing of medical images. (April 2019) - Aggarwal, Ashutosh; Sharma, Suchita; Singh, Karamjeet; Singh, Harpreet; Kumar, Sunil
Highlights: OFMMs-based biomedical image retrieval approach proposed. Experiments performed on both noisy and noise-free CT and MR images of four test databases. Retrieval performance of the proposed method is far better than the existing as well as recently published approaches. Average improvement of 7% in case of noise free images by the proposed approach over the existing approaches. Average improvement of 20% in case of noisy images by the proposed approach over the existing approaches. Abstract: The use of medical imaging has increased manifold in past decade. The medical images have become more and more informative about the patient's anatomy. Thus, the medical images are now not only used for diagnosis purpose but also stored for R&D purpose in order to have better understanding and deeper insights into the cause and cure of various diseases. 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 paper 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 favorable 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, NEMA MRI and OASIS MRI. Additional experiments have been conducted to analyze the noise robustness ability of the proposed and all the compared approaches. The reported results show a significant increase of about 7% and 20% (average) in the retrieval rate of the proposed approach over all the existing approaches on noise free and noisy images, respectively, of all four test medical databases.