TitleEpidermis area detection for immunofluorescence microscopy
Publication typeConference paper
Author(s)A.Dovganich, A.Krylov, A.Nasonov, N.Makhneva
Publication date2017
Conference9th International Conference on Graphics and Image Processing (IGCIP 2017)
Page(s)1061522
AbstractWe propose a novel image segmentation method for immunofluorescence microscopy images of skin tissue for the diagnosis of various skin diseases. The segmentation is based on machine learning algorithms. The feature vector is filled by three groups of features: statistical features, Laws’ texture energy measures and local binary patterns. The images are preprocessed for better learning. Different machine learning algorithms have been used and the best results have been obtained with random forest algorithm. We use the proposed method to detect the epidermis region as a part of pemphigus diagnosis system.
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