NDLI: Accumulated grey-level image representation for classification of lung cancer genetic mutations employing 2D principle component analysis

Content Provider	IET Digital Library
Author	Abdelrahman, S. A. Abdelwahab, M. M.
Abstract	Lung cancer is an insidious disease, producing no symptoms until the disease spreads widely in the human body. Mutations of genes are the first alarm of such a disease in the human body. Therefore, classifying these mutations could provide guidance for the treatment decisions for lung cancer. In this Letter, a novel accumulated grey-level image (AGLI) method for gene representation is introduced, where each base in gene sequence is represented by accumulated number based on its order in gene sequence and then reflected into image domain. AGLI is incorporated with 2D principle component analysis to build accurate and low-dimensional algorithm for classifying the genetic mutations. Proposed algorithm was applied on the top 10 effective genes in lung cancer, where an accuracy of 99.27% was achieved. Experimental results show that the proposed algorithm enhanced the accuracy of classification and reduced the classification time for mutation in lung cancer relative to the existing methods.
Starting Page	194
Ending Page	196
Page Count	3
ISSN	00135194
Volume Number	54
e-ISSN	1350911X
Issue Number	Issue 4, Feb (2018)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/el/54/4
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/el.2017.1890
Journal	Electronics Letters
Publisher Date	2018-01-05
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	2D Principle Component Analysis Accumulated Grey-level Image Method Accumulated Grey-level Image Representation AGLI Method Biology And Medical Computing Cancer Computer Vision And Image Processing Technique Gene Mutations Gene Representation Gene Sequence Image Domain Image Representation Insidious Disease Low-dimensional Algorithm Lung Lung Cancer Genetic Mutations Medical Image Processing Optical, Image And Video Signal Processing Patient Care And Treatment Patient Diagnostic Method And Instrumentation Patient Treatment Principal Component Analysis Probability Theory Statistics Stochastic Linearised SCUC Treatment Decisions
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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