A Features Fusion Approach for Neonatal and Pediatrics Brain Tumor Image Analysis Using Genetic and Deep Learning Techniques

Prashantha Sj,H.N Prakash

doi:10.3991/ijoe.v17i11.25193

Abstract

<p class="0abstract">Nowadays, Deep learning (DL) is the growing trend towards creating visual representations of human body organs for clinical analysis, medical interventions as well as to diagnose and treat diseases. This paper propose a method for neonatal and pediatric brain tumors image analysis and prerequisites a T2- weighted MR images only. The pipeline stages of the proposed work as follows: In the first stage, designed a set of specific feature vectors description for high-level classification task using Conventional and deep learning (DL) Feature Extraction methods. The second stage, select a deep features based on proposed convolutional neural network (CNN) method and conventional subset features are from Genetic Algorithm (GA). The third stage, merge the selected features by adapting fusion technique. Finally, predict the brain image is either normal or abnormal. The results demonstrated that the proposed method obtained accurate classification and revealed its robustness to difference in ages and acquisition protocols. The obtained results shows that based on combined deep learning features (DLF) and conventional features have been significantly improves the classification accuracy of the support vector machines (SVM) classifier up to 97.00%.</p>

Highlights

Medical imaging is the process of creating visual representations of the body
In the experiments of Genetic Algorithm Feature Selection (GAFS) model, genetic algorithm is extensively used for feature selection and outcome is strongly dependent on population diversity and selective pressure
The fitness of an individual is determined by evaluating the neural network constructed in GAFS method and outputs an optimal subset of features

Summary

Introduction

Medical imaging is the process of creating visual representations of the body. The human brain is one of the unique and largest complex organs in the central nervous system (CNS). Medical imaging contributes to an anatomy database representing internal and external structures of the body, making it easier to identify abnormalities of the human brain. According to world health organization (WHO), one -in -six deaths globally due to cancer and estimated 9.6 million deaths in 2018.More than 80% of the 200,000 new childhood cancers occur annually in developing world [1]. Brain cancer or tumor is one of the serious diseases in the life of human brain development and it is an abnormal growth of cells in the brain. There are several unlike or dissimilar brains anatomical and mechanical functioning are present in neonatal period, infancy, childhood and adult’s brain

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