Automatic segmentation of chromatographic images for region of interest delineation

• Type: Article in International Conference Proceedings Book
• Date: 2011

Authors

Ana M Mendonca (Author) FEUP; Antonio V Sousa (Author) Other; Clara C Sa Miranda (Author) Other; Aurelio C Campilho (Author) FEUP

Conference proceedings International

Title: MEDICAL IMAGING 2011: IMAGE PROCESSING

Final page: 79623B

Conference on Medical Imaging 2011 - Image Processing

Lake Buena Vista, FL, FEB 14-16, 2011

Indexing

ISI Proceedings

ISI Web of Knowledge - 0 Citations

Scopus - 3 Citations

Scientific classification

FOS: Engineering and technology > Electrical engineering, Electronic engineering, Information engineering

Other information

Authenticus ID: P-002-XBJ

DOI: 10.1117/12.877671

Abstract (EN): 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.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 7