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Proceedings Paper

Detection of anomaly in human retina using Laplacian Eigenmaps and vectorized matched filtering
Author(s): Karamatou A. Yacoubou Djima; Lucia D. Simonelli; Denise Cunningham; Wojciech Czaja
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Paper Abstract

We present a novel method for automated anomaly detection on auto fluorescent data provided by the National Institute of Health (NIH). This is motivated by the need for new tools to improve the capability of diagnosing macular degeneration in its early stages, track the progression over time, and test the effectiveness of new treatment methods. In previous work, macular anomalies have been detected automatically through multiscale analysis procedures such as wavelet analysis or dimensionality reduction algorithms followed by a classification algorithm, e.g., Support Vector Machine. The method that we propose is a Vectorized Matched Filtering (VMF) algorithm combined with Laplacian Eigenmaps (LE), a nonlinear dimensionality reduction algorithm with locality preserving properties. By applying LE, we are able to represent the data in the form of eigenimages, some of which accentuate the visibility of anomalies. We pick significant eigenimages and proceed with the VMF algorithm that classifies anomalies across all of these eigenimages simultaneously. To evaluate our performance, we compare our method to two other schemes: a matched filtering algorithm based on anomaly detection on single images and a combination of PCA and VMF. LE combined with VMF algorithm performs best, yielding a high rate of accurate anomaly detection. This shows the advantage of using a nonlinear approach to represent the data and the effectiveness of VMF, which operates on the images as a data cube rather than individual images.

Paper Details

Date Published: 20 March 2015
PDF: 11 pages
Proc. SPIE 9413, Medical Imaging 2015: Image Processing, 94132F (20 March 2015); doi: 10.1117/12.2082482
Show Author Affiliations
Karamatou A. Yacoubou Djima, Univ. of Maryland, College Park (United States)
Lucia D. Simonelli, Univ. of Maryland, College Park (United States)
Denise Cunningham, National Institutes of Health (United States)
Wojciech Czaja, Univ. of Maryland, College Park (United States)

Published in SPIE Proceedings Vol. 9413:
Medical Imaging 2015: Image Processing
Sébastien Ourselin; Martin A. Styner, Editor(s)

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