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Title

DIMENSIONALITY REDUCTION OF MRI DATA USING A GENETICALLY OPTIMIZED NEURAL NETWORK

Pages

  35-49

Keywords

Not Registered.

Abstract

 In this paper, a method of dimensionality reduction for MR image sequence data of brain, to a three-dimensional space is presented. Reduction of dimensions is motivated by the need to visualize the distribution of data and interactively segment the MR image sequence. New feature space is extracted using a non-linear neural network. A genetic algorithm is used to search for the neural network parameters such that the transformed data in the network output optimize a specific objective function. Three objective functions are proposed based on Sammons cost function where in two of them a constraint is added to the cost function. The data in the three-dimensional (3-D) output feature space is visualized using the perspective image of the 3-D histogram. MR images are segmented interactively by determining the cluster centers in the perspective image. The results of the proposed methods are compared with those of Linear Transformation and Back-Propagation Neural Network (BPNN) methods. For simulated MR images, two of the proposed criterions produce better results in terms of cluster separation. Based on 10 real MR image sequence data, the same two criterions result in lower segmentation error rates.

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    APA: Copy

    MOHAMMADI, A., & SOLTANIANZADEH, H.. (2004). DIMENSIONALITY REDUCTION OF MRI DATA USING A GENETICALLY OPTIMIZED NEURAL NETWORK. JOURNAL OF FACULTY OF ENGINEERING (UNIVERSITY OF TEHRAN), 38(1 (83)), 35-49. SID. https://sid.ir/paper/14567/en

    Vancouver: Copy

    MOHAMMADI A., SOLTANIANZADEH H.. DIMENSIONALITY REDUCTION OF MRI DATA USING A GENETICALLY OPTIMIZED NEURAL NETWORK. JOURNAL OF FACULTY OF ENGINEERING (UNIVERSITY OF TEHRAN)[Internet]. 2004;38(1 (83)):35-49. Available from: https://sid.ir/paper/14567/en

    IEEE: Copy

    A. MOHAMMADI, and H. SOLTANIANZADEH, “DIMENSIONALITY REDUCTION OF MRI DATA USING A GENETICALLY OPTIMIZED NEURAL NETWORK,” JOURNAL OF FACULTY OF ENGINEERING (UNIVERSITY OF TEHRAN), vol. 38, no. 1 (83), pp. 35–49, 2004, [Online]. Available: https://sid.ir/paper/14567/en

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