Classification on Alzheimers Disease MRI Images with VGG-16 and VGG-19

Title

Classification on Alzheimers Disease MRI Images with VGG-16 and VGG-19

Creator

Antony F.; Anita H.B.; George J.A.

Description

Balancing thoughts and memories of our life is indeed the most critical part of the human brain.Thus, its stability and sustenance are also important for smooth functioning.The changes in the structure can lead to disorders such as dementia and one such type of condition is known as Alzheimers disease.Multi modal neuroimaging like magnetic resonance imaging (MRI) and positron emission tomography (PET) is used for the early diagnosis of Alzheimers disease (AD) by providing complementary information.Different modalities like PET and MRI data were acquired from the same subject, there exists markable materiality between MRI and PET data.Mild cognitive impairment (MCI) is the initial stage with few symptoms of AD.To recognise the subjects which are capable of converting from MCI to AD is to be analysed for further treatments.In this research, specific convolutional neural networks (CNN) which are designed for classifications like VGG-16 and VGG-19 deep learning architectures were used to check the accuracy of cognitively normal (CN) versus MCI, CN versus AD and MCI to AD conversion using MRI data.The proposed research is analysed and tested using MRI data from Alzheimers disease neuroimaging initiative (ADNI). 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Source

Smart Innovation, Systems and Technologies, Vol-312, pp. 199-207.

Date

2023-01-01

Publisher

Springer Science and Business Media Deutschland GmbH

Subject

Alzheimers disease (AD); Cognitively normal (CN); Mild cognitive impairment (MCI); Visual geometry group (VGG) and convolutional neural networks (CNN)

Coverage

Antony F., Department of Computer Science, Christ (Deemed to be University), Karnataka, Bangalore, India; Anita H.B., Department of Computer Science, Christ (Deemed to be University), Karnataka, Bangalore, India; George J.A., Department of Life Sciences, Christ (Deemed to be University), Karnataka, Bangalore, India

Rights

Restricted Access

Relation

ISSN: 21903018; ISBN: 978-981193574-9

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1007/978-981-19-3575-6_22

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85140766920&doi=10.1007%2f978-981-19-3575-6_22&partnerID=40&md5=8c98779138dd08a4151f44d7f6057671