scroll to top
0

EBSCO Auth Banner

Let's find your institution. Click here.

Advanced Search Results For "Goo-Rak Kwon"

1 - 10 of 166 results for
 "Goo-Rak Kwon"
Results per page:

A novel scaled-gamma-tanh (SGT) activation function in 3D CNN applied for MRI classification

Publication Type: Academic Journal

Source(s): Scientific Reports, Vol 12, Iss 1, Pp 1-14 (2022)

Abstract: Abstract Activation functions in the neural network are responsible for ‘firing’ the nodes in it. In a deep neural network they ‘activate’ the features to reduce feature redundancy and learn the complex pattern by adding non-linearity in the network to...

Subjects:
View details

Automated Detection of Alzheimer’s Disease and Mild Cognitive Impairment Using Whole Brain MRI

Publication Type: Academic Journal

Source(s): IEEE Access, Vol 10, Pp 65055-65066 (2022)

Abstract: Early diagnosis is critical for the development and success of interventions, and neuroimaging is one of the most promising areas for early detection of Alzheimer’s disease (AD). This study is aimed to develop a deep learning method to extract valuable...

View details

Alzheimer’s Disease Diagnosis and Biomarker Analysis Using Resting-State Functional MRI Functional Brain Network With Multi-Measures Features and Hippocampal Subfield and Amygdala Volume of Structural MRI

Publication Type: Academic Journal

Source(s): Frontiers in Aging Neuroscience, Vol 14 (2022)

Abstract: Accurate diagnosis of the initial phase of Alzheimer’s disease (AD) is essential and crucial. The objective of this research was to employ efficient biomarkers for the diagnostic analysis and classification of AD based on combining structural MRI (sMRI...

View details

SIP-UNet: Sequential Inputs Parallel UNet Architecture for Segmentation of Brain Tissues from Magnetic Resonance Images

Publication Type: Academic Journal

Source(s): Mathematics, Vol 10, Iss 2755, p 2755 (2022)

Abstract: Proper analysis of changes in brain structure can lead to a more accurate diagnosis of specific brain disorders. The accuracy of segmentation is crucial for quantifying changes in brain structure. In recent studies, UNet-based architectures have outper...

View details

Classification of Alzheimer’s Disease Based on Core-Large Scale Brain Network Using Multilayer Extreme Learning Machine

Publication Type: Academic Journal

Source(s): Mathematics, Vol 10, Iss 1967, p 1967 (2022)

Abstract: Various studies suggest that the network deficit in default network mode (DMN) is prevalent in Alzheimer’s disease (AD) and mild cognitive impairment (MCI). Besides DMN, some studies reveal that network alteration occurs in salience network motor netwo...

View details

Classification of Alzheimer’s Disease and Mild-Cognitive Impairment Base on High-Order Dynamic Functional Connectivity at Different Frequency Band

Publication Type: Academic Journal

Source(s): Mathematics, Vol 10, Iss 805, p 805 (2022)

Abstract: Functional brain connectivity networks obtained from resting-state functional magnetic resonance imaging (rs-fMRI) have been extensively utilized for the diagnosis of Alzheimer’s disease (AD). However, the traditional correlation analysis technique onl...

View details

Diagnosis of Alzheimer’s Disease Using Brain Network

Publication Type: Academic Journal

Source(s): Frontiers in Neuroscience, Vol 15 (2021)

Abstract: Recent studies suggest the brain functional connectivity impairment is the early event occurred in case of Alzheimer’s disease (AD) as well as mild cognitive impairment (MCI). We model the brain as a graph based network to study these impairment. In th...

View details

3D CNN Design for the Classification of Alzheimer’s Disease Using Brain MRI and PET

Publication Type: Academic Journal

Source(s): IEEE Access, Vol 8, Pp 217830-217847 (2020)

Abstract: Attempt to diagnose Alzheimer's disease (AD) using imaging modalities is one of the scopes of deep learning. While considering the theoretical background from past studies, we are trying to identify convolutional neural network (CNN) behaviors moving f...

View details

VBM-Based Alzheimer’s Disease Detection from the Region of Interest of T1 MRI with Supportive Gaussian Smoothing and a Bayesian Regularized Neural Network

Publication Type: Academic Journal

Source(s): Applied Sciences, Vol 11, Iss 6175, p 6175 (2021)

Abstract: This paper presents an efficient computer-aided diagnosis (CAD) approach for the automatic detection of Alzheimer’s disease in patients’ T1 MRI scans using the voxel-based morphometry (VBM) analysis of the region of interest (ROI) in the brain. The ide...

View details

Classification and Graphical Analysis of Alzheimer’s Disease and Its Prodromal Stage Using Multimodal Features From Structural, Diffusion, and Functional Neuroimaging Data and the APOE Genotype

Publication Type: Academic Journal

Source(s): Frontiers in Aging Neuroscience, Vol 12 (2020)

Abstract: Graphical, voxel, and region-based analysis has become a popular approach to studying neurodegenerative disorders such as Alzheimer’s disease (AD) and its prodromal stage [mild cognitive impairment (MCI)]. These methods have been used previously for cl...

View details
sponsored