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IEEE 754 Floating Point Pipelined Multiplier with Karatsuba for Mitigations of Area and Power Read chapter Read first chapter

2021 | OriginalPaper | Chapter

An Artificially Intelligent Fusion Approach for Prognosis of Alzheimer’s Disease

Authors : Suranjana Mukherjee, Arpita Das

Published in: Computers and Devices for Communication

Publisher: Springer Singapore

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Abstract

In the present study, we have merged functional and anatomical information to study the prognosis of Alzheimer’s disease (AD). To restore all possible directional information of the source images, the shift-invariant non-subsampled shearlet transform (NSST)-based decomposition technique is employed. Then, principle component analysis (PCA) and position-based maximum energy selection scheme are applied for lower subband and higher subbands, respectively, to combine multimodal information in a single frame. Finally, fused images have been generated by inverse NSST. Efficiency of the proposed fusion scheme has been reflected in the experimental results.

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previous chapter Automatic Detection and Classification of Enhanced Brain Tumor Using Machine Learning Algorithm
next chapter System Stability Performance Analysis on an Artificial Lower Limb
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Metadata
Title
An Artificially Intelligent Fusion Approach for Prognosis of Alzheimer’s Disease
Authors
Suranjana Mukherjee
Arpita Das
Copyright Year
2021
Publisher
Springer Singapore
Book
Computers and Devices for Communication

Print ISBN: 978-981-15-8365-0

Electronic ISBN: 978-981-15-8366-7

Copyright Year: 2021

DOI
https://doi.org/10.1007/978-981-15-8366-7_7