RETRACTED ARTICLE: Medical image integrated possessions assisted soft computing techniques for optimized image fusion with less noise and high contour detection

This paper introduces an intellectual image fusion technique which is much focused on Medical Image Integrated Possessions assisted Soft Computing Techniques (MIPSCT) with fuzzy sets. This dual image fusion design uses a fuzzy mid matrix method and a smooth adjustment process which helps to eliminat...

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Bibliographic Details
Published inJournal of ambient intelligence and humanized computing Vol. 12; no. 6; pp. 6811 - 6824
Main Authors Mithya, V., Nagaraj, B.
Format Journal Article
LanguageEnglish
Published Berlin/Heidelberg Springer Berlin Heidelberg 01.06.2021
Springer Nature B.V
Subjects
Algorithms
Artificial Intelligence
Computational Intelligence
Computer vision
Contours
Data compression
Engineering
Fuzzy sets
Genetic algorithms
Image processing
Mathematical models
Matrix methods
Medical imaging
Modelling
Neural networks
Neuroimaging
Optimization
Original Research
Parameters
Robotics and Automation
Signal to noise ratio
Soft computing
Software
Tomography
User Interfaces and Human Computer Interaction
Medical image processing
Data learning process
Fuzzy mid matrix
Soft computing
Intelligent image fusion
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Summary:This paper introduces an intellectual image fusion technique which is much focused on Medical Image Integrated Possessions assisted Soft Computing Techniques (MIPSCT) with fuzzy sets. This dual image fusion design uses a fuzzy mid matrix method and a smooth adjustment process which helps to eliminate impulsive noise from extremely distorted images that is included in a smart image agent when fusing image on various image processing environment. The fuzzy function used in the filter is intended to remove impulses without losing fine details and textures which are more important in image fusion modelling. Furthermore, adjust filter parameters from a set of exercise data with an image culture process based on genetic algorithm has been implemented on MIPSCT to improve contour detection. The experimental results have been analyzed based on intelligent soft computing tools in assistance with matrix laboratory to achieve better output in accordance with SDROM, AWFM, SFVQ, and DCT modelling for brain image datasets. The validation at lab scale shows promising results on Peak Signal to Noise Ratio and Absolute Mean Error (AME) parameters in accordance with conventional methods.
Bibliography:retraction
ISSN:1868-5137
1868-5145
DOI:10.1007/s12652-020-02316-0