NDLI: AiMRS: A feature extraction method from MRS signals based on artificial immune algorithms for classification of brain tumours

Content Provider	IET Digital Library
Author	Dandil, Emre
Abstract	Precise diagnosis of brain tumour by experienced radiologists involves a complex set of processes including magnetic resonance imaging, magnetic resonance spectroscopy (MRS) data and histopathological evaluations. In this study, a new hybrid feature extraction method, called as aiMRS, based on the negative selection algorithm and clonal selection algorithm of artificial immune systems is developed on MRS data for the detection and classification of brain tumours. In the study, differentiation of benign and malignant brain tumours, classification of normal brain tissue and brain tumour, and detection of metastasis and primary brain tumours are performed with high precision using pattern recognition methods based on the proposed aiMRS method. According to the experimental results performed on a large data set created with the MRS data obtained from INTERPRET database, when the proposed feature extraction method applied, classification of normal brain tissue and brain tumours, benign and malignant brain tumours and metastasis and primary brain tumours is achieved with 100, 98.58 and 98.94% accuracy, respectively. These results show that this proposed system can be used as a secondary tool in physicians' decision-making processes for the classification of brain tumours.
Starting Page	361
Ending Page	373
Page Count	13
ISSN	17519675
Volume Number	14
e-ISSN	17519683
Issue Number	Issue 6, Aug (2020)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-spr/14/6
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-spr.2019.0576
Journal	IET Signal Processing
Publisher Date	2020-04-23
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Artificial Immune System Benign Brain Tumours Biology And Medical Computing Biomedical Magnetic Resonance Imaging Biomedical MRI Brain Brain Tumour Cancer Computer Vision And Image Processing Technique Feature Extraction Hybrid Feature Extraction Method Knowledge Engineering Technique Magnetic Resonance Spectroscopy Magnetic Resonance Spectroscopy Data Malignant Brain Tumours Medical Image Processing Medical Magnetic Resonance Imaging And Spectroscopy MRS Data Normal Brain Tissue Optical, Image And Video Signal Processing Patient Diagnosis Patient Diagnostic Method And Instrumentation Pattern Recognition Primary Brain Tumours Spectroscopy Statistics Tumours
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering

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