Proposed System for Detection of Alzheimer’s Disease

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Published: Feb 26, 2020
DOI: https://doi.org/10.26483/ijarcs.v11i1.6503
Keywords:
ADNI, Alzheimer’s Disease, Convolution Neural Networks, Deep Learning, Image Processing

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Siddhi Raajjhesh Bothraa
Fr. C. Rodrigues Institute of Technology affiliated to the University of Mumbai
Jonathan Bob Jackson
Fr. C. Rodrigues Institute of Technology affiliated to the University of Mumbai
Shruti Telang
Fr. C. Rodrigues Institute of Technology affiliated to the University of Mumbai

Abstract

Alzheimer's disease is a neurological disorder in which the death of brain cells causes memory loss and cognitive decline. It is a type of dementia that gradually destroys brain cells, affecting a person's memory. It is an irreversible, progressive brain disorder that slowly destroys memory, thinking skills and the ability to carry out the simplest tasks. Alzheimer's disease is the most common cause of dementia among older adults. Pre-detection is crucial for such a disease as drugs will be most effective if administered early in the course of the disease. If not done on time, it can lead to irreversible brain damage. Therefore, it is very important to utilize automated techniques for pre-detection of Alzheimer's symptoms from such data. The system uses an experimental approach to evaluate the best pre-detection method of Alzheimer’s disease. The study consists of two parts. First is obtaining the Alzheimer’s disease Neuroimaging Initiative (ADNI) dataset and performing Image Processing on it which will be used to train the system. Next is using a Deep Learning algorithm to detect the disease from this neuroimaging data.

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Vol. 11 No. 1 (2020): Volume 11, No. 1, January-February 2020
Section
Articles

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Author Biographies

Siddhi Raajjhesh Bothraa, Fr. C. Rodrigues Institute of Technology affiliated to the University of Mumbai

Department of Computer Engineering

Jonathan Bob Jackson, Fr. C. Rodrigues Institute of Technology affiliated to the University of Mumbai

Department of Computer Engineering

Shruti Telang, Fr. C. Rodrigues Institute of Technology affiliated to the University of Mumbai

Department of Computer Engineering

References

https://www.healthline.com/health/alzheimers-disease-complications#complications

R. Anitha, Prakash and S. Jyothi, "A segmentation technique to detect the Alzheimer's disease using image processing," 2016 International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT), Chennai, 2016, pp.

Islam, Jyoti, and Yanqing Zhang. “Brain MRI analysis for Alzheimer's disease diagnosis using an ensemble system of deep convolutional neural networks.†Brain informatics vol. 5,2 2. 31 May. 2018

Gunawardena, K., Rajapakse, R., & Kodikara, N.D. (2017). “Applying convolutional neural networks for pre-detection of Alzheimer’s disease from structural MRI data.†2017 24th International Conference on Mechatronics and Machine Vision in Practice (M2VIP), 1-7

https://www.researchgate.net/post/in_simple_words_what_do_you_mean_by_feature_vector_in_image_processing

http://adni.loni.usc.edu/

Mr. B.Venkateswara Reddy, Dr. P. Bhaskara Reddy, Dr. P. Satish Kumar , Dr. S. Siva Reddy “Developing an Approach to Brain MRI Image Preprocessing for Tumor Detection†International Journal of Research (IJR) Vol-1, Issue-6, July 2014