Deep 3D Convolutional Neural Network Architectures for Alzheimer’s Disease Diagnosis

Hiroki Karasawa*, Chien-Liang Liu, Hayato Ohwada

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

9 Scopus citations

Abstract

Dementia has become a social problem in the aging society of advanced countries. Currently, 46.8 million people have dementia worldwide, and that figure is predicted to increase threefold to 130 million people by 2050. Alzheimer’s disease (AD) is the most common form of dementia. The cost of care for AD patients in 2015 was 818 billion US dollars and is expected to increase dramatically in the future, due to the increasing number of patients as a result of the aging society. However, it is still very difficult to cure AD; thus, the detection of AD is crucial. This study proposes the use of machine learning to detect AD using brain image data, with the goal of reducing the cost of diagnosing and caring for AD patients. Most machine learning algorithms rely on good feature representations, which are commonly obtained manually and require domain experts to provide guidance. Feature extraction is a time-consuming and labor-intensive task. In contrast, the 3D Convolutional Neural Network (3DCNN) automatically learns feature representation from images and is not greatly affected by image processing. However, the performance of CNN depends on its layer architecture. This study proposes a novel 3DCNN architecture for MRI image diagnosis of AD.

Original languageEnglish
Title of host publicationIntelligent Information and Database Systems - 10th Asian Conference, ACIIDS 2018, Proceedings
EditorsHoang Pham, Ngoc Thanh Nguyen, Bogdan Trawinski, Duong Hung Hoang, Tzung-Pei Hong
PublisherSpringer Verlag
Pages287-296
Number of pages10
ISBN (Print)9783319754161
DOIs
StatePublished - 1 Jan 2018
Event10th International scientific conferences on research and applications in the field of intelligent information and database systems, ACIIDS 2018 - Dong Hoi City, Viet Nam
Duration: 19 Mar 201821 Mar 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10751 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference10th International scientific conferences on research and applications in the field of intelligent information and database systems, ACIIDS 2018
CountryViet Nam
CityDong Hoi City
Period19/03/1821/03/18

Keywords

  • 3D Convolutional Neural Network
  • Alzheimer’s disease diagnosis
  • Deep residual network
  • Image processing
  • Machine learning

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