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Title: Multispectral medical image fusion in Contourlet domain for computer based diagnosis of Alzheimer’s disease

Abstract

Computer based diagnosis of Alzheimer’s disease can be performed by dint of the analysis of the functional and structural changes in the brain. Multispectral image fusion deliberates upon fusion of the complementary information while discarding the surplus information to achieve a solitary image which encloses both spatial and spectral details. This paper presents a Non-Sub-sampled Contourlet Transform (NSCT) based multispectral image fusion model for computer-aided diagnosis of Alzheimer’s disease. The proposed fusion methodology involves color transformation of the input multispectral image. The multispectral image in YIQ color space is decomposed using NSCT followed by dimensionality reduction using modified Principal Component Analysis algorithm on the low frequency coefficients. Further, the high frequency coefficients are enhanced using non-linear enhancement function. Two different fusion rules are then applied to the low-pass and high-pass sub-bands: Phase congruency is applied to low frequency coefficients and a combination of directive contrast and normalized Shannon entropy is applied to high frequency coefficients. The superiority of the fusion response is depicted by the comparisons made with the other state-of-the-art fusion approaches (in terms of various fusion metrics).

Authors:
; ;  [1];  [2];  [3];  [2];  [4]
  1. Shri Ramswaroop Memorial Group of Professional Colleges (SRMGPC), Lucknow, Uttar Pradesh 226028 (India)
  2. Duytan University, Danang 550000 (Viet Nam)
  3. Department of Innovation Engineering, University of Salento, Lecce 73100 (Italy)
  4. (Viet Nam)
Publication Date:
OSTI Identifier:
22597755
Resource Type:
Journal Article
Resource Relation:
Journal Name: Review of Scientific Instruments; Journal Volume: 87; Journal Issue: 7; Other Information: (c) 2016 Author(s); Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND TECHNOLOGY; 75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND SUPERFLUIDITY; ALGORITHMS; BRAIN; COMPARATIVE EVALUATIONS; DIAGNOSIS; DISEASES; ENTROPY; IMAGES; NONLINEAR PROBLEMS

Citation Formats

Bhateja, Vikrant, E-mail: bhateja.vikrant@gmail.com, E-mail: nhuongld@hus.edu.vn, Moin, Aisha, Srivastava, Anuja, Bao, Le Nguyen, Lay-Ekuakille, Aimé, Le, Dac-Nhuong, E-mail: bhateja.vikrant@gmail.com, E-mail: nhuongld@hus.edu.vn, and Haiphong University, Haiphong 180000. Multispectral medical image fusion in Contourlet domain for computer based diagnosis of Alzheimer’s disease. United States: N. p., 2016. Web. doi:10.1063/1.4959559.
Bhateja, Vikrant, E-mail: bhateja.vikrant@gmail.com, E-mail: nhuongld@hus.edu.vn, Moin, Aisha, Srivastava, Anuja, Bao, Le Nguyen, Lay-Ekuakille, Aimé, Le, Dac-Nhuong, E-mail: bhateja.vikrant@gmail.com, E-mail: nhuongld@hus.edu.vn, & Haiphong University, Haiphong 180000. Multispectral medical image fusion in Contourlet domain for computer based diagnosis of Alzheimer’s disease. United States. doi:10.1063/1.4959559.
Bhateja, Vikrant, E-mail: bhateja.vikrant@gmail.com, E-mail: nhuongld@hus.edu.vn, Moin, Aisha, Srivastava, Anuja, Bao, Le Nguyen, Lay-Ekuakille, Aimé, Le, Dac-Nhuong, E-mail: bhateja.vikrant@gmail.com, E-mail: nhuongld@hus.edu.vn, and Haiphong University, Haiphong 180000. 2016. "Multispectral medical image fusion in Contourlet domain for computer based diagnosis of Alzheimer’s disease". United States. doi:10.1063/1.4959559.
@article{osti_22597755,
title = {Multispectral medical image fusion in Contourlet domain for computer based diagnosis of Alzheimer’s disease},
author = {Bhateja, Vikrant, E-mail: bhateja.vikrant@gmail.com, E-mail: nhuongld@hus.edu.vn and Moin, Aisha and Srivastava, Anuja and Bao, Le Nguyen and Lay-Ekuakille, Aimé and Le, Dac-Nhuong, E-mail: bhateja.vikrant@gmail.com, E-mail: nhuongld@hus.edu.vn and Haiphong University, Haiphong 180000},
abstractNote = {Computer based diagnosis of Alzheimer’s disease can be performed by dint of the analysis of the functional and structural changes in the brain. Multispectral image fusion deliberates upon fusion of the complementary information while discarding the surplus information to achieve a solitary image which encloses both spatial and spectral details. This paper presents a Non-Sub-sampled Contourlet Transform (NSCT) based multispectral image fusion model for computer-aided diagnosis of Alzheimer’s disease. The proposed fusion methodology involves color transformation of the input multispectral image. The multispectral image in YIQ color space is decomposed using NSCT followed by dimensionality reduction using modified Principal Component Analysis algorithm on the low frequency coefficients. Further, the high frequency coefficients are enhanced using non-linear enhancement function. Two different fusion rules are then applied to the low-pass and high-pass sub-bands: Phase congruency is applied to low frequency coefficients and a combination of directive contrast and normalized Shannon entropy is applied to high frequency coefficients. The superiority of the fusion response is depicted by the comparisons made with the other state-of-the-art fusion approaches (in terms of various fusion metrics).},
doi = {10.1063/1.4959559},
journal = {Review of Scientific Instruments},
number = 7,
volume = 87,
place = {United States},
year = 2016,
month = 7
}
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