MRI and PET Image Fusion Using Fuzzy Logic and Image Local Features

An image fusion technique for magnetic resonance imaging (MRI) and positron emission tomography (PET) using local features and fuzzy logic is presented. The aim of proposed technique is to maximally combine useful information present in MRI and PET images. Image local features are extracted and comb...

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Detalles Bibliográficos
Autores principales: Javed, Umer, Riaz, Muhammad Mohsin, Ghafoor, Abdul, Ali, Syed Sohaib, Cheema, Tanveer Ahmed
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2014
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3916105/
https://www.ncbi.nlm.nih.gov/pubmed/24574912
http://dx.doi.org/10.1155/2014/708075
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author Javed, Umer
Riaz, Muhammad Mohsin
Ghafoor, Abdul
Ali, Syed Sohaib
Cheema, Tanveer Ahmed
author_facet Javed, Umer
Riaz, Muhammad Mohsin
Ghafoor, Abdul
Ali, Syed Sohaib
Cheema, Tanveer Ahmed
author_sort Javed, Umer
collection PubMed
description An image fusion technique for magnetic resonance imaging (MRI) and positron emission tomography (PET) using local features and fuzzy logic is presented. The aim of proposed technique is to maximally combine useful information present in MRI and PET images. Image local features are extracted and combined with fuzzy logic to compute weights for each pixel. Simulation results show that the proposed scheme produces significantly better results compared to state-of-art schemes.
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spelling pubmed-39161052014-02-26 MRI and PET Image Fusion Using Fuzzy Logic and Image Local Features Javed, Umer Riaz, Muhammad Mohsin Ghafoor, Abdul Ali, Syed Sohaib Cheema, Tanveer Ahmed ScientificWorldJournal Research Article An image fusion technique for magnetic resonance imaging (MRI) and positron emission tomography (PET) using local features and fuzzy logic is presented. The aim of proposed technique is to maximally combine useful information present in MRI and PET images. Image local features are extracted and combined with fuzzy logic to compute weights for each pixel. Simulation results show that the proposed scheme produces significantly better results compared to state-of-art schemes. Hindawi Publishing Corporation 2014-01-19 /pmc/articles/PMC3916105/ /pubmed/24574912 http://dx.doi.org/10.1155/2014/708075 Text en Copyright © 2014 Umer Javed et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Javed, Umer
Riaz, Muhammad Mohsin
Ghafoor, Abdul
Ali, Syed Sohaib
Cheema, Tanveer Ahmed
MRI and PET Image Fusion Using Fuzzy Logic and Image Local Features
title MRI and PET Image Fusion Using Fuzzy Logic and Image Local Features
title_full MRI and PET Image Fusion Using Fuzzy Logic and Image Local Features
title_fullStr MRI and PET Image Fusion Using Fuzzy Logic and Image Local Features
title_full_unstemmed MRI and PET Image Fusion Using Fuzzy Logic and Image Local Features
title_short MRI and PET Image Fusion Using Fuzzy Logic and Image Local Features
title_sort mri and pet image fusion using fuzzy logic and image local features
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3916105/
https://www.ncbi.nlm.nih.gov/pubmed/24574912
http://dx.doi.org/10.1155/2014/708075
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