IJEE (International Journal of Engineering Education)
Vol 1, No 1 (2019)

A Robust Grey Wolf-based Deep Learning for Brain Tumour Detection in MR Images

Geetha A. Geetha (Unknown)
Gomathi N. Gomathi (Unknown)



Article Info

Publish Date
15 Jun 2019

Abstract

In recent times, the detection of brain tumour is a common fatality in the field of the health community. Generally, the brain tumor is an abnormal mass of tissue where the cells grow up and increase uncontrollably, apparently unregulated by mechanisms that control cells. A number of techniques have been developed so far; however, the time consumption in detecting brain tumor is still a challenge in the field of image processing.  This paper intends to propose a new detection model even accurately. The model includes certain processes like Preprocessing, Segmentation, Feature Extraction and Classification. Particularly, two extreme processes like contrast enhancement and skull stripping are processed under initial phase, in the segmentation process, this paper uses Fuzzy Means Clustering (FCM) algorithm. Both Gray Level Co-occurrence Matrix (GLCM) as well as Gray-Level Run-Length Matrix (GRLM) features are extracted in feature extraction phase. Moreover, this paper uses Deep Belief Network (DBN) for classification. The DBN is integrated with the optimization approach, and hence this paper introduces the optimized DBN, for which Grey Wolf Optimization (GWO) is used here.  The proposed model is termed as GW-DBN model. The proposed model compares its performance over other conventional methods in terms of Accuracy, Specificity, Sensitivity, Precision, Negative Predictive Value (NPV), F1Score and Matthews Correlation Coefficient (MCC), False negative rate (FNR), False positive rate (FPR) and False Discovery Rate (FDR), and proven the superiority of proposed work. 

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Journal Info

Abbrev

ijee

Publisher

Subject

Education Engineering

Description

The scope of journal covers all area in a wide variety of research areas in the field of engineering education. Some of research area such as (1) engineering epistemologies (what constitutes engineering thinking and knowledge), (2) engineering learning mechanisms (how learners develop knowledge and ...