A New Optimized Hybrid Local Lifting Wavelet Co-occurrence Texture Pattern for Content Based Medical Image Retrieval

Authors

  • R Varaprasada Rao "Jawaharlal Nehru Technological University Anantapur (JNTUA)"
  • T Jaya Chandra Prasad "Rajeev Gandhi Memorial College of Engineering and Technology (RGMCET)", Nandyal, Andhra Pradesh, India

DOI:

https://doi.org/10.3991/ijoe.v17i11.25351

Keywords:

Medical image retrieval, Local tetra pattern, Gradient directional pattern, lifting wavelet transform, Equilibrium optimization

Abstract


Medical image retrieval (MIR) is a hard task owing to the varied patterns and structures in the medical images. The feature descriptors have been used to describe the images in most MIR approaches. Based on the local relationship, several feature descriptors of neighbouring image pixels have been proposed for MIR so far, but their low performance scores make them unsuitable. In this paper, an efficient optimized hybrid local lifting wavelet co-occurrence texture pattern for content-based MIR is proposed. Initially, image resize and Adaptive histogram equalization technique is used to carried out for contrast enhancement. Then Local Lifting Wavelet Co-occurrence Texture Pattern is derived using Local tetra pattern, Gradient directional pattern, lifting wavelet transform and Gray level co-occurrence matrix. An Equilibrium optimization technique is employed to select the most important features of an image from the obtained feature vectors (FV). Finally, to match the query image with the database images, distance between their FV is computed and the minimum distance images are considered as retrieval outcome. Three benchmark medical databases of various modalities (CT and MRI) are used to test the efficiency of the proposed method: EXACT-09, TCIA-CT, and OASIS. The experimental results prove that the proposed approach outperforms existing descriptors in terms of APR and ARR.

Author Biographies

R Varaprasada Rao, "Jawaharlal Nehru Technological University Anantapur (JNTUA)"

Research Scholar, Department of Electronics and communication Engineering

T Jaya Chandra Prasad, "Rajeev Gandhi Memorial College of Engineering and Technology (RGMCET)", Nandyal, Andhra Pradesh, India

Professor, Department of Electronics and communication Engineering

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Published

2021-11-15

How to Cite

Varaprasada Rao, R., & Jaya Chandra Prasad, T. (2021). A New Optimized Hybrid Local Lifting Wavelet Co-occurrence Texture Pattern for Content Based Medical Image Retrieval. International Journal of Online and Biomedical Engineering (iJOE), 17(11), pp. 157–175. https://doi.org/10.3991/ijoe.v17i11.25351

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Papers