Detecting Alzheimer disease in magnetic resonance brain images using gabor wavelets
2007 IEEE 15th Signal Processing and Communications Applications
Abstract
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This 2007 IEEE conference paper by Ulas Bagci and Li Bai describes an approach using Gabor wavelet features and support vector machines to classify brain MR images.
Summary
The paper presents a method for classifying magnetic resonance (MR) brain images using Gabor features extracted at multiple scales and orientations. The authors describe using these features with support vector machines to distinguish images associated with Alzheimer disease from normal brain MR images. The abstract reports experimental results, including 100% classification performance for a combination of three scales and eight orientations; the available record does not provide enough evaluation detail to interpret this figure as evidence of clinical diagnostic performance.
Cite this work
Ulas Bagci; Li Bai (2007). Detecting Alzheimer disease in magnetic resonance brain images using gabor wavelets. 2007 IEEE 15th Signal Processing and Communications Applications https://doi.org/10.1109/SIU.2007.4298553
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