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

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

4 Citations (Scopus)
495 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.
Original languageEnglish
Title of host publicationComputer Analysis of Images and Patterns
Number of pages9
ISBN (Electronic)978-3-319-23192-1
ISBN (Print)978-3-319-23191-4
Publication statusPublished - 2015
Event16th International Conference on Computer Analysis of Images and Patterns - Valletta, Malta
Duration: 2-Sep-20154-Sep-2015

Publication series

NameLecture Notes in Computer Science
PublisherSpringer International Publishing


Conference16th International Conference on Computer Analysis of Images and Patterns


  • Serration patterns analysis
  • direct immunofluorescence image
  • COSFIRE filter
  • ridge detection
  • skin disease

Cite this