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Neural Computing and Applications
Published in: Neural Computing and Applications 12/2018

29-03-2017 | Original Article

Morphological segmenting and neighborhood pixel-based locality preserving projection on brain fMRI dataset for semantic feature extraction: an affective computing study

Authors: Zongmei Tian, Nilanjan Dey, Amira S. Ashour, Pamela McCauley, Fuqian Shi

Published in: Neural Computing and Applications | Issue 12/2018

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Abstract

Two specific chemical receptive fields of brain, namely the amygdala and the orbital-frontal cortex, are related to valence and arousal in medical experiments. Functional magnetic resonance imaging (fMRI), which is a noninvasive, repeatable, and atomical tool for medical imaging in clinic system, was widely used in affective computing; however, it faces its dataset processing difficulty for dimensional reduction as well as for decreasing the computational complexity. In addition, features extraction from those de-dimensionality datasets is a challenging issue. The current work solved the de-dimensionality issue by using some preprocessing algorithms including clustering, morphological segmenting, and locality preserving projection. In order to keep useful information in fMRI dataset for reduction process, improved neighborhood pixel-based locality preserving projection (NP-LPP) algorithm was addressed and continuously for feature extraction operating using Otsu weighted sum of histogram. Furthermore, a modified covariance power spectral density (MC-PSD) separately in an fMRI Valence–Arousal experiments was measured. The results were analyzed and compared with affective norms English words system. The experiments established that the proposed methods of NP-LPP effectively simplified high complexity of fMRI, and Otsu weighted sum of histogram exhibited superior performance for features extraction compared to the MC-PSD through the calculation root mean standard error. The current proposed method provided a potential application and promising research direction on human semantic retrieval through medical imaging dataset.
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Metadata
Title
Morphological segmenting and neighborhood pixel-based locality preserving projection on brain fMRI dataset for semantic feature extraction: an affective computing study
Authors
Zongmei Tian
Nilanjan Dey
Amira S. Ashour
Pamela McCauley
Fuqian Shi
Publication date
29-03-2017
Publisher
Springer London
Published in
Neural Computing and Applications / Issue 12/2018
Print ISSN: 0941-0643
Electronic ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-017-2955-2

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