Big Medical Image Analysis: Alzheimer’s Disease Classification Using Convolutional Autoencoder

Authors

  • Padmini Mansingh Department of Computer Science and Engineering Institute of Technical Education and Research (ITER) Siksha 'O' Anusandhan (Deemed to be University) Bhubaneswar, Odisha, INDIA
  • Binod Kumar Pattanayak Department of Computer Science and Engineering Institute of Technical Education and Research (ITER) Siksha 'O' Anusandhan (Deemed to be University) Bhubaneswar, Odisha, INDIA
  • Bibudhendu Pati Rama Devi Women's University

DOI:

https://doi.org/10.13053/cys-26-4-4090

Keywords:

Deep Learning, Big Data Analytics, CANN, ICA, Healthcare, Machine Leaning

Abstract

Deep learning-based analysis is a noticeable topic in recent years. The enormous success of deep learning is now combined with big data analytics to provide an open platform to the health care industry for a better diagnosis of any disease. In this paper, we described the convolutional autoencoder technique that reduces the complexity of radiologists through a brief study of Alzheimer's MRI data which led to a rise in data-driven medical research for a better diagnosis. In this research, we have compared the effects of two techniques: convolutional autoencoder (CANN) and independent component analysis (ICA), and discovered that CANN has a higher accuracy of 98.8% and outperforms ICA models in terms of convergence speed.

Author Biography

Bibudhendu Pati, Rama Devi Women's University

Bibudhendu Pati is the Head in the Department of Computer Science at Rama Devi Women’s University (only Govt. Women’s University in the State of Odisha, India). He received his Bachelor in Engineering in Computer Science degree with Honours, Master in Engineering in Computer Science from National Institute of Technical Teachers' Training and Research (NITTTR), Chandigarh, Panjab, India, PhD degree from Indian Institute of Technology (IIT) Kharagpur, India. He has around 23 years of experience in teaching and research. His current research interests include Wireless Sensor Networks, Mobile Cloud Computing, Big Data, Internet of Things, and Advanced Network Technologies. He has been involved in many professional and editorial activities.  He has got several papers published in reputed journals, conference proceedings, and books of International repute. He also served as Guest Editor of many reputed journals. He was the General Chair of ICACIE 2016, IEEE ANTS 2017, ICACIE 2018, ICACIE 2019, and ICACIE 2020 International Conferences. He has developed Advanced Network Technologies and Software Engineering Virtual Lab available online. He is the Life Member of Indian Society for Technical Education (ISTE), Life Member of Computer Society of India (CSI), and Senior Member of IEEE.

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Published

2022-12-25

Issue

Vol. 26 No. 4 (2022): 26(4) 2022

Section

Articles

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