An empirical study of digital signal filtering to improve Alzheimer’s disease detection

Cindy Gonzales; Benjamin M. Rodriguez

doi:10.1117/12.2643563

3 October 2022 An empirical study of digital signal filtering to improve Alzheimer’s disease detection

Cindy Gonzales, Benjamin M. Rodriguez

Proceedings Volume 12227, Applications of Machine Learning 2022; 122270Q (2022) https://doi.org/10.1117/12.2643563
Event: SPIE Optical Engineering + Applications, 2022, San Diego, California, United States

Abstract

According to the Alzheimer’s Association, roughly one in nine people age 65 and older suffer from the burden of Alzheimer’s dementia and one in three seniors dies with Alzheimer’s or another dementia. Recent advances have been made in early diagnosis of Alzheimer’s Disease including utilizing machine learning techniques to identify abnormalities associated with Alzheimer’s Disease in magnetic resonance imaging (MRI) data. In this paper, we will explore how the pre-processing of two-dimensional (2D) slices of MRI data using digital signal processing techniques affect a machine learning classifier. This work differs from other studies as it focuses on the methods used to pre-process the MRI data to highlight abnormalities rather than optimizing the machine learning approach based on the available data provided. We show that employing digital signal processing techniques, specifically low-pass and high-pass filtering, to 2D slices of an MRI in the frequency domain can improve the performance of a basic machine learning classifier. This is a promising result which has the potential to improve the performance of state-of-the-art machine learning classifiers simply by pre-processing the data using a digital signal/image filter.

Conference Presentation

Citation Download Citation

Cindy Gonzales and Benjamin M. Rodriguez "An empirical study of digital signal filtering to improve Alzheimer’s disease detection", Proc. SPIE 12227, Applications of Machine Learning 2022, 122270Q (3 October 2022); https://doi.org/10.1117/12.2643563

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