MRI and CT image indexing and retrieval using local mesh peak valley edge patterns

作者：Murala Subrahmanyam; Wu Q M Jonathan^*

来源：Signal Processing: Image Communication , 2014, 29(3): 400-409.

DOI：10.1016/j.image.2013.12.002

• Medical imaging
• Image retrieval
• Patterns
• Texture
• Local binary patterns (LBP)

In this paper, a new pattern based feature, local mesh peak valley edge pattern (LMePVEP) is proposed for biomedical image indexing and retrieval. The standard LBP extracts the gray scale relationship between the center pixel and its surrounding neighbors in an image. Whereas the proposed method extracts the gray scale relationship among the neighbors for a given center pixel in an image. The relations among the neighbors are peak/valley edges which are obtained by performing the first-order derivative. The performance of the proposed method (LMePVEP) is tested by conducting two experiments on two benchmark biomedical databases. Further, it is mentioned that the databases used for experiments are OASIS-MRI database which is the magnetic resonance imaging (MRI) database and VIA/I-ELCAP-CT database which includes region of interest computer tomography (CT) images. The results after being investigated show a significant improvement in terms average retrieval precision (ARP) and average retrieval rate (ARR) as compared to LBP and LBP variant features.

• 出版日期2014-3