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Proceedings Paper

Automatic segmentation of chromatographic images for region of interest delineation
Author(s): Ana M. Mendonça; António V. Sousa; M. Clara Sá-Miranda; Aurélio C. Campilho
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Paper Abstract

This paper describes a segmentation method for automating the region of interest (ROI) delineation in chromatographic images, thus allowing the definition of the image area that contains the fundamental information for further processing while excluding the frame of the chromatographic plate that does not contain relevant data for disease identification. This is the first component of a screening tool for Fabry disease, which will be based on the automatic analysis of the chromatographic patterns extracted from the image ROI. Image segmentation is performed in two phases, where each individual pixel is finally considered as frame or ROI. In the first phase, an unsupervised learning method is used for classifying image pixels into three classes: frame, ROI or unknown. In the second phase, distance features are used for deciding which class the unknown pixels belong to. The segmentation result is post-processed using a sequence of morphological operators in order to obtain the final ROI rectangular area. The proposed methodology was successfully evaluated in a dataset of 41 chromatographic images.

Paper Details

Date Published: 14 March 2011
PDF: 7 pages
Proc. SPIE 7962, Medical Imaging 2011: Image Processing, 79623B (14 March 2011); doi: 10.1117/12.877671
Show Author Affiliations
Ana M. Mendonça, Univ. do Porto (Portugal)
António V. Sousa, Univ. do Porto (Portugal)
M. Clara Sá-Miranda, IBMC - Instituto de Biologia Molecular e Celular (Portugal)
Aurélio C. Campilho, Univ. do Porto (Portugal)

Published in SPIE Proceedings Vol. 7962:
Medical Imaging 2011: Image Processing
Benoit M. Dawant; David R. Haynor, Editor(s)

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