Immunofluorescence diagnosis and analysis of samples of its images in autoimmune pemphigus

Abstract

Autoimmune Pemphigus is a group of autoimmune bullous dermatosis characterized by intraepithelial blister formation and the presence of specific IgG-antibodies to the antigens of the intercellular bonding substance (MCC) stratified squamous epithelium. Specific immunomorphological picture (fixing IgG in MCC epidermis) allows to diagnose this bullous dermatosis. However, in some cases, during the use of this diagnostic method visualization of specific features is difficult because of the use of mild and/or non-uniform specific immunohistochemical reaction that prevents to diagnose pemphigus with absolute precision. The analysis of immunofluorescence diagnosis in autoimmune pemphigus was performed. Skin tissue image analysis algorithm is proposed. The algorithm performs image quality enhancement and detects inter-cell structures that are typical for pemphigus assessment. The algorithm consists of alignment illumination, median filtering, Gaussian filter processing, ridge detection using Hessian, image binarization, separation, for a ridge map, connected components and removing components with a small radius. In cases of doubt this allows to differentiate and diagnose autoimmune pemphigus. In addition, a clear visualization of character (granular or linear) fixing the immunoglobulin class G in the intercellular spaces of the epidermis increases the accuracy of the prediction of further disease progression (favorable or torpid) providing timely and appropriate management of the patient prescribing pathogenetic treatment regimens. This work emphasizes importance of introducing the modern computer methods of medical images, that allow significantly to improve the methods of diagnosis of human diseases, including autoimmune bullous dermatosis.

Keywords

autoimmune pemphigus / immunofluorescence / image processing / ridge detection

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