A Novel AI-Based System for Detection and Severity Prediction of Dementia Using MRI

Dementia is a symptom of Alzheimer’s Disease (A.D.) that affects many people around the globe each year. There is no effective cure to treat this disease, and it can prove to be deadly to the patient if left untreated or undetected. In this paper, the authors propose a novel DCGAN-based A...

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Autores principales:	Varun Jain, Om Nankar, Daryl Jacob Jerrish, Shilpa Gite, Shruti Patil, Ketan Kotecha
Formato:	article
Lenguaje:	EN
Publicado:	IEEE 2021
Materias:	Augmentation dementia generative adversarial networks magnetic resonance imaging mild cognitive impairment Electrical engineering. Electronics. Nuclear engineering TK1-9971
Acceso en línea:	https://doaj.org/article/737dc31d64f64522a05f283342f7efac
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spelling	oai:doaj.org-article:737dc31d64f64522a05f283342f7efac2021-11-24T00:02:52ZA Novel AI-Based System for Detection and Severity Prediction of Dementia Using MRI2169-353610.1109/ACCESS.2021.3127394https://doaj.org/article/737dc31d64f64522a05f283342f7efac2021-01-01T00:00:00Zhttps://ieeexplore.ieee.org/document/9611247/https://doaj.org/toc/2169-3536Dementia is a symptom of Alzheimer’s Disease (A.D.) that affects many people around the globe each year. There is no effective cure to treat this disease, and it can prove to be deadly to the patient if left untreated or undetected. In this paper, the authors propose a novel DCGAN-based Augmentation and Classification (D-BAC) model approach to identify and classify dementia into various categories depending upon its prominence and severity in the available MRI scans. The proposed detection of early onset of dementia, also referred to as Mild Cognitive Impairment (MCI), is also studied with the help of a novel GAN-augmented dataset. The proposed model can predict MCI with an accuracy of 74% and can classify dementia into four categories depending upon its prominence in the MRI scan. The authors have also utilized Visual Explainable A.I. (XAI) and have used GradCAM to visually represent the internal working of the model. This novel approach helps verify the differentiating features of the MRI scans learned by the CNN model during training. Three different datasets, namely the original dataset, geometrically transformed images, and a GAN-augmented dataset, have been used for performance analysis. A comparison of the performance of the CNN model has been made on these datasets, and the superiority of results using the novel GAN-augmented dataset has been studied and discussed. Moreover, progressive resizing has also been applied on this GAN-dataset, and different CNN architectures have also been used to achieve better performance scores. The model proposed in the end has a training accuracy of 97% and a testing accuracy of 82% when tested using a conventional CNN architecture and has a testing accuracy of 84% and 87% when tested using VGG-16 and VGG-19 architecture, respectively.Varun JainOm NankarDaryl Jacob JerrishShilpa GiteShruti PatilKetan KotechaIEEEarticleAugmentationdementiagenerative adversarial networksmagnetic resonance imagingmild cognitive impairmentElectrical engineering. Electronics. Nuclear engineeringTK1-9971ENIEEE Access, Vol 9, Pp 154324-154346 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Augmentation dementia generative adversarial networks magnetic resonance imaging mild cognitive impairment Electrical engineering. Electronics. Nuclear engineering TK1-9971
spellingShingle	Augmentation dementia generative adversarial networks magnetic resonance imaging mild cognitive impairment Electrical engineering. Electronics. Nuclear engineering TK1-9971 Varun Jain Om Nankar Daryl Jacob Jerrish Shilpa Gite Shruti Patil Ketan Kotecha A Novel AI-Based System for Detection and Severity Prediction of Dementia Using MRI
description	Dementia is a symptom of Alzheimer’s Disease (A.D.) that affects many people around the globe each year. There is no effective cure to treat this disease, and it can prove to be deadly to the patient if left untreated or undetected. In this paper, the authors propose a novel DCGAN-based Augmentation and Classification (D-BAC) model approach to identify and classify dementia into various categories depending upon its prominence and severity in the available MRI scans. The proposed detection of early onset of dementia, also referred to as Mild Cognitive Impairment (MCI), is also studied with the help of a novel GAN-augmented dataset. The proposed model can predict MCI with an accuracy of 74% and can classify dementia into four categories depending upon its prominence in the MRI scan. The authors have also utilized Visual Explainable A.I. (XAI) and have used GradCAM to visually represent the internal working of the model. This novel approach helps verify the differentiating features of the MRI scans learned by the CNN model during training. Three different datasets, namely the original dataset, geometrically transformed images, and a GAN-augmented dataset, have been used for performance analysis. A comparison of the performance of the CNN model has been made on these datasets, and the superiority of results using the novel GAN-augmented dataset has been studied and discussed. Moreover, progressive resizing has also been applied on this GAN-dataset, and different CNN architectures have also been used to achieve better performance scores. The model proposed in the end has a training accuracy of 97% and a testing accuracy of 82% when tested using a conventional CNN architecture and has a testing accuracy of 84% and 87% when tested using VGG-16 and VGG-19 architecture, respectively.
format	article
author	Varun Jain Om Nankar Daryl Jacob Jerrish Shilpa Gite Shruti Patil Ketan Kotecha
author_facet	Varun Jain Om Nankar Daryl Jacob Jerrish Shilpa Gite Shruti Patil Ketan Kotecha
author_sort	Varun Jain
title	A Novel AI-Based System for Detection and Severity Prediction of Dementia Using MRI
title_short	A Novel AI-Based System for Detection and Severity Prediction of Dementia Using MRI
title_full	A Novel AI-Based System for Detection and Severity Prediction of Dementia Using MRI
title_fullStr	A Novel AI-Based System for Detection and Severity Prediction of Dementia Using MRI
title_full_unstemmed	A Novel AI-Based System for Detection and Severity Prediction of Dementia Using MRI
title_sort	novel ai-based system for detection and severity prediction of dementia using mri
publisher	IEEE
publishDate	2021
url	https://doaj.org/article/737dc31d64f64522a05f283342f7efac
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A Novel AI-Based System for Detection and Severity Prediction of Dementia Using MRI

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