In this paper, a robust sparse representation for medical image classification is proposed
based on the adaptive type-2 fuzzy learning (T2-FDL) system. In the proposed method …

In this paper, an Automated Brain Image Analysis (ABIA) system that classifies the Magnetic
Resonance Imaging (MRI) of human brain is presented. The classification of MRI images …

Purpose The most complex organ in the human body is the brain. The unrestrained growth
of cells in the brain is called a brain tumor. The cause of a brain tumor is still unknown and …

A non-invasive diagnostic support system for brain cancer diagnosis is presented in this
study. Recently, very deeper convolution neural networks are designed for computerized …

Recent developments in medical image analysis techniques make them essential tools in
medical diagnosis. Medical imaging is always involved with different kinds of uncertainties …

Sparse coding allows the representation of complex data as a linear combination of basis
sparse vectors (alternatively called atoms or codewords), a collection of which constitutes a …

The advancement of automated medical diagnosis in biomedical engineering has become
an important area of research. Image classification is one of the diagnostic approaches that …

Brain tumours are composed of cells where the growth is unrestrained. Though the
incidence rate is lower, it is a serious threatening disease to human lives. For effective …

Abstract In this study, Deep Neural Network (DNN) with Pyramid Design (PD) is developed
for brain image classification. The main objective is to design a non-invasive procedure for …

The aim of this research is to determine the effectiveness of using CT Scans in Early
Detection of Brain Tumors. The type of research is meta-analysis research. The data sources …