130 research outputs found

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

    Get PDF
    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

    Automatic classification of serrated patterns in direct immunouorescence images

    Get PDF
    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.peer-reviewe

    Diagnosis of pemphigoid diseases

    Get PDF

    Diagnosis of pemphigoid diseases

    Get PDF

    Diagnosis of pemphigoid diseases

    Get PDF

    Serration pattern analysis for differentiating epidermolysis bullosa acquisita from other pemphigoid diseases

    Get PDF
    Background: Direct immunofluorescence (DIF) microscopy of a skin biopsy specimen is the reference standard for the diagnosis of pemphigoid diseases (PDs). Serration pattern analysis enables the differentiation of epidermolysis bullosa acquisita (EBA) from other PDs using DIF microscopy alone. However, practice gaps need to be addressed in order to implement this technique in the routine diagnostic procedure. Objective: We sought to determine and optimize the technical requirements for serration pattern analysis of DIF microscopy and determine interrater conformity of serration pattern analysis. Methods: We compared serration pattern analysis of routine DIF microscopy from laboratories in Groningen, The Netherlands and Lubeck, Germany with 4 blinded observers. Skin biopsy specimens from 20 patients with EBA and other PDs were exchanged and analyzed. Various factors were evaluated, including section thickness, transport medium, and biopsy specimen processing. Results: The interrater conformity of our 4 observers was 95.7%. Recognition of serration patterns was comparable in samples transported in saline and in Michel's medium and with section thicknesses of 4, 6, and 8 mu m. Limitations: Limitations include our small sample size and the availability of 20 samples that were compared retrospectively. Conclusion: DIF serration pattern analysis is not restricted by variation in laboratory procedures, transport medium, or experience of observers. This learnable technique can be implemented as a routine diagnostic method as an extension of DIF microscopy for subtyping PD. (J Am Acad Dermatol 2018;78:754-9.
    corecore