Automatic differentiation of u- and n-serrated patterns in direct immunofluorescence images

Chenyu Shi, Jiapan Guo, George Azzopardi, Joost Meijer, Marcel F. Jonkman, Nicolai Petkov

OnderzoeksoutputAcademicpeer review

4 Citaten (Scopus)
469 Downloads (Pure)


Epidermolysis bullosa acquisita (EBA) is a subepidermal autoimmune blistering disease of the skin. Manual u- and n-serrated patterns analysis in direct immunofluorescence (DIF) images is used in medical practice to differentiate EBA from other forms of pemphigoid. The manual analysis of serration patterns in DIF images is very challenging, mainly due to noise and lack of training of the immunofluorescence (IF) microscopists. There are no automatic techniques to distinguish these two types of serration patterns. We propose an algorithm for the automatic recognition of such a disease. We first locate a region where u- and n-serrated patterns are typically found. Then, we apply a bank of B-COSFIRE filters to the identified region of interest in the DIF image in order to detect ridge contours. This is followed by the construction of a normalized histogram of orientations. Finally, we classify an image by using the nearest neighbors algorithm that compares its normalized histogram of orientations with all the images in the dataset. The best results that we achieve on the UMCG publicly available data set is 84.6% correct classification, which is comparable to the results of medical experts.
Originele taal-2English
TitelComputer Analysis of Images and Patterns
Aantal pagina's9
ISBN van elektronische versie978-3-319-23192-1
ISBN van geprinte versie978-3-319-23191-4
StatusPublished - 2015
Evenement16th International Conference on Computer Analysis of Images and Patterns - Valletta, Malta
Duur: 2-sep-20154-sep-2015

Publicatie series

NaamLecture Notes in Computer Science
UitgeverijSpringer International Publishing


Conference16th International Conference on Computer Analysis of Images and Patterns

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