A Transfer Learning Approach to Classify the Brain Age from MRI Images

Animesh Kumar, Pramod Pathak, Paul Stynes

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

Abstract

Predicting brain age from Magnetic Resonance Imaging (MRI) can be used to identify neurological disorders at an early stage. The brain contour is a biomarker for the onset of brain-related problems. Artificial Intelligence (AI) based Convolutional Neural Networks (CNN) is used to detect brain-related problems in MRI images. However, conventional CNN is a complex architecture and the time to process the image, large data requirement and overfitting are some of its challenges. This study proposes a transfer learning approach using InceptionV3 to classify brain age from the MRI images in order to improve the brain age classification model. Models are trained on an augmented OASIS (Open Access Series of Imaging Studies) dataset which contains 411 raw and 411 masked MRI images of different people. The models are evaluated using testing accuracy, precision, recall, and F1-Scores. Results demonstrate that InceptionV3 has a testing accuracy of 85%. This result demonstrates the potential for InceptionV3 to be used by medical practitioners to detect brain age and the potential onset of neurological disorders from MRI images.

Original languageEnglish
Title of host publicationBig Data Analytics - 8th International Conference, BDA 2020, Proceedings
EditorsLadjel Bellatreche, Vikram Goyal, Hamido Fujita, Anirban Mondal, P. Krishna Reddy
PublisherSpringer Science and Business Media Deutschland GmbH
Pages103-112
Number of pages10
ISBN (Print)9783030666644
DOIs
Publication statusPublished - 2020
Externally publishedYes
Event8th International Conference on Big Data Analytics, BDA 2020 - Sonepat, India
Duration: 15 Dec 202018 Dec 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12581 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference8th International Conference on Big Data Analytics, BDA 2020
Country/TerritoryIndia
CitySonepat
Period15/12/2018/12/20

Keywords

  • Brain age
  • InceptionV3
  • MRI images
  • Neurological disorder
  • Transfer learning

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