Classification of Elastic and Collagen Fibers in H&E Stained Hyperspectral Images

This study investigates the classification performance of elastic and collagen fibers using H&E stained hyperspectral images. As many as 1200 sample pixels were trained by using Linear discriminant analysis (LDA) and support vector machine (SVM) methods for reduction and classification. The classification result both using LDA and SVM show that H&E stained hyperspectral images performed better classification than H&E stained RGB image by comparing the classification of EVG stained images visually and quantitatively.