Texture Analysis Using Modified Computational Model of Grating Cells in Content-Based Medical Image Retrieval

Authors:
Gang Zhang;Z. M. Ma;Zhiping Cai;Hailong Wang
Affiliations:
College of Information Science and Engineering, Northeastern University, Shenyang, China 110004 and School of Software Engineering, Shenyang University of Technology, Shenyang, China 110004;College of Information Science and Engineering, Northeastern University, Shenyang, China 110004;College of Information Science and Engineering, Northeastern University, Shenyang, China 110004;College of Information Science and Engineering, Northeastern University, Shenyang, China 110004
Venue:
Medical Imaging and Informatics
Year:
2008

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Abstract

In neuroscience, grating cells in areas V1 and V2 of the visual cortex of monkeys can respond vigorously to a grating of bars of appropriate orientation, position and periodicity. Computational models of grating cells have been proposed and used to make texture analysis for medical images. To improve the matching precision, the computation models of grating cells were applied to the responses of simple cells and not for the pixel values of the input image. In this paper, the computational models of grating cells is modified to express uncertain information. Multi-valued logic is introduced into the computation of the responses of the grating subunit. Texture pattern is computed by means of the modified computational model of grating cells. Experiments show that the content-based medical image retrieval system using the modified computational model of grating cells has good performance.