MRI and CT image indexing and retrieval using local mesh peak valley edge patterns |
| |
| Affiliation: | 1. CSE Department, JCDMCOE, Sirsa, Haryana, India;2. Computer Engineering Department, NIT, Kurukshetra, Haryana, India;3. CSE Department, GJUS&T, Hisar, Haryana, India;1. Division of Computer and Telecommunications Engineering, Yonsei University, Gangwon 220-710, Republic of Korea;2. Samsung Electronics Corporation, Gyeonggi 443-803, Republic of Korea;3. Department of Information and Communication Engineering, Hanbat National University, Daejeon 305-719, Republic of Korea;4. Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL 32611, USA |
| |
| Abstract: | 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. |
| |
| Keywords: | Medical imaging Image retrieval Patterns Texture Local binary patterns (LBP) |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
