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Proceedings Paper

Classification of microscopy images of Langerhans islets
Author(s): Jan Švihlík; Jan Kybic; David Habart; Zuzana Berková; Peter Girman; Jan Kříž; Klára Zacharovová
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Paper Abstract

Evaluation of images of Langerhans islets is a crucial procedure for planning an islet transplantation, which is a promising diabetes treatment. This paper deals with segmentation of microscopy images of Langerhans islets and evaluation of islet parameters such as area, diameter, or volume (IE). For all the available images, the ground truth and the islet parameters were independently evaluated by four medical experts. We use a pixelwise linear classifier (perceptron algorithm) and SVM (support vector machine) for image segmentation. The volume is estimated based on circle or ellipse fitting to individual islets. The segmentations were compared with the corresponding ground truth. Quantitative islet parameters were also evaluated and compared with parameters given by medical experts. We can conclude that accuracy of the presented fully automatic algorithm is fully comparable with medical experts.

Paper Details

Date Published: 21 March 2014
PDF: 8 pages
Proc. SPIE 9034, Medical Imaging 2014: Image Processing, 90341S (21 March 2014); doi: 10.1117/12.2043621
Show Author Affiliations
Jan Švihlík, Czech Technical Univ. in Prague (Czech Republic)
Jan Kybic, Czech Technical Univ. in Prague (Czech Republic)
David Habart, Institute for Clinical and Experimental Medicine (Czech Republic)
Zuzana Berková, Institute for Clinical and Experimental Medicine (Czech Republic)
Peter Girman, Institute for Clinical and Experimental Medicine (Czech Republic)
Jan Kříž, Institute for Clinical and Experimental Medicine (Czech Republic)
Klára Zacharovová, Institute for Clinical and Experimental Medicine (Czech Republic)


Published in SPIE Proceedings Vol. 9034:
Medical Imaging 2014: Image Processing
Sebastien Ourselin; Martin A. Styner, Editor(s)

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