Automatic Classification of Serrated Patterns in Direct Immunofluorescence Images

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

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademic


Direct immunofluorescence (DIF) images are used by clinical experts for the diagnosis of autoimmune blistering diseases. The analysis of serration patterns in DIF images concerns two types of patterns, namely n- and u-serrated. Manual analysis is time-consuming and challenging due to noise. We propose an algorithm for the automatic classification of serrated patterns in DIF images. We first segment the epidermal basement membrane zone (BMZ) where n- and u-serrated patterns are typically found. Then, we apply a bank of B-COSFIRE filters to detect ridges and determine their orientations with respect to the BMZ. Finally, we classify an image by comparing its normalized histogram of relative orientations with those of the training images using a nearest neighbor approach. We achieve a recognition rate of 84.4% on a UMCG data set of 416 DIF images, which is comparable to 83.4% by clinical experts.
Original languageEnglish
Title of host publication Autonomous Systems 2015 - Proceedings of the 8th GI Conference
PublisherVDI Verlag
Number of pages9
ISBN (Print)978-3-18-384210-0
Publication statusPublished - 2015
EventAutonomous Systems 2015-the 8th GI Conference - Hotel Sabina Playa C/ Es Rafal nº 4,07560, Cala Millor, Spain
Duration: 25-Oct-201530-Oct-2015

Publication series

NameFortschritt-Berichte VDI. Informatik/Kommunikationstechnik
ISSN (Print)0178-9627


ConferenceAutonomous Systems 2015-the 8th GI Conference
CityCala Millor


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

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