Zobrazeno 1 - 10 of 19 pro vyhledávání: '"Bijen Khagi"'
1
Akademický článek
A novel scaled-gamma-tanh (SGT) activation function in 3D CNN applied for MRI classification
Autor: Bijen Khagi, Goo-Rak Kwon
Publikováno v: Scientific Reports, Vol 12, Iss 1, Pp 1-14 (2022)
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
Externí odkaz: https://doaj.org/article/abba5826c72341c6b4fbd0ec386f50dd
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2
Akademický článek
3D CNN based Alzheimer’s diseases classification using segmented Grey matter extracted from whole-brain MRI
Autor: Bijen Khagi, Goo-Rak Kwon
Publikováno v: JOIV: International Journal on Informatics Visualization, Vol 5, Iss 2, Pp 200-205 (2021)
A recent study from MRI has revealed that there is a minor increase in cerebral-spinal fluid (CSF) content in brain ventricles and sulci, along with a substantial decrease in grey matter (GM) content and brain volume among Alzheimer's disease (AD) pa
Externí odkaz: https://doaj.org/article/3b1e65456a7c4ad2bfeb7dcc52ea933a
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3
Akademický článek
Convolutional Neural Network-Based Natural Image and MRI Classification Using Gaussian Activated Parametric (GAP) Layer
Autor: Bijen Khagi, Goo Rak Kwon
Publikováno v: IEEE Access, Vol 9, Pp 96930-96947 (2021)
We propose a novel gaussian activated parametric (GAP) layer for deep neural networks specifically for CNN. This layer normalizes the feature vector using the Gaussian filter-based un-sharpening technique. The goal of the proposed method is to normal
Externí odkaz: https://doaj.org/article/9c9c6e110dcd416d8a948ee5fb615aba
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4
Akademický článek
3D CNN Design for the Classification of Alzheimer’s Disease Using Brain MRI and PET
Autor: Bijen Khagi, Goo-Rak Kwon
Publikováno v: IEEE Access, Vol 8, Pp 217830-217847 (2020)
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
Externí odkaz: https://doaj.org/article/7ece7ad116e64b0d8191d46165f55733
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5
Akademický článek
VBM-Based Alzheimer’s Disease Detection from the Region of Interest of T1 MRI with Supportive Gaussian Smoothing and a Bayesian Regularized Neural Network
Autor: Bijen Khagi, Kun Ho Lee, Kyu Yeong Choi, Jang Jae Lee, Goo-Rak Kwon, Hee-Deok Yang
Publikováno v: Applied Sciences, Vol 11, Iss 13, p 6175 (2021)
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. T
Externí odkaz: https://doaj.org/article/1601083d51ce41869126c7411bf60f63
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8
3D CNN Design for the Classification of Alzheimer’s Disease Using Brain MRI and PET
Autor: Goo-Rak Kwon, Bijen Khagi
Publikováno v: IEEE Access. 8:217830-217847
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 movi
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::0a48183878af1e5e332db3b51b58a74b
https://doi.org/10.1109/access.2020.3040486
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