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1 2002

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Texture analysis of fluorescence microscopic images of tissue

Atlamazoglou V., Yova D.

Image Processing & Communications

2002

Vol. 8, no 2

105-111

The aim of this study was to assess the potential of texture analysis for the characterization of fluorescence images from colonic tissue sections stained with a novel and selective fluoroprobe, Rhodamine B-phenylboronic acid. Fluorescence microscopy images of colonic healthy mucosa (n=35) and adenocarcinomas (n=35) were digitally captured and subjected to image texture analysis. Textural features derived from the grey level cooccurrence matrix were calculated. A modified version of the multiple discriminant analysis criterion was used to choose an appropriate subset of features. A minimum Mahalanobis distance, linear discriminant classifier was used to classify image feature data into the two categories. A subset of four textural features was selected and used for the description and classification of each image field. They were found appropriate to correctly classify 95% of the images into the two classes. These features contained information about local homogeneity and grey level linear dependencies of the image.