Classification of microscopy images of Langerhans islets
Typ dokumentu
ArticleAutor
Švihlík, Jan
Kybic, Jan
Habart, David
Berková, Zuzana
Girman, Peter
Kříž, Jan
Zacharovová, Klára
Práva
Copyright 2014 Society of Photo Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic electronic or print reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.Metadata
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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 classi er (perceptron algorithm) and SVM (support vector machine) for image segmentation. The volume is estimated based on circle or ellipse tting 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.
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