Search results for "IIF images"
showing 6 items of 6 documents
Automatic Segmentation of HEp-2 Cells Based on Active Contours Model
2018
In the past years, a great deal of effort was put into research regarding Indirect Immunofluorescence techniques with the aim of development of CAD systems. In this work a method for segmenting HEp-2 cells in IIF images is presented. Such task is one of the most challenging of automated IIF analysis, because the segmentation algorithm has to cope with a large heterogeneity of shapes and textures. In order to address this problem, numerous techniques and their combinations were evaluated, in a process aimed at maximizing the figure of merit. The proposed method, for a greater definition of cellular contours, uses the active contours in the last phase of the process. The initial conditions, c…
An Automatic HEp-2 Specimen Analysis System Based on an Active Contours Model and an SVM Classification
2019
The antinuclear antibody (ANA) test is widely used for screening, diagnosing, and monitoring of autoimmune diseases. The most common methods to determine ANA are indirect immunofluorescence (IIF), performed by human epithelial type 2 (HEp-2) cells, as substrate antigen. The evaluation of ANA consist an analysis of fluorescence intensity and staining patterns. This paper presents a complete and fully automatic system able to characterize IIF images. The fluorescence intensity classification was obtained by performing an image preprocessing phase and implementing a Support Vector Machines (SVM) classifier. The cells identification problem has been addressed by developing a flexible segmentati…
Deep CNN for IIF Images Classification in Autoimmune Diagnostics
2019
The diagnosis and monitoring of autoimmune diseases are very important problem in medicine. The most used test for this purpose is the antinuclear antibody (ANA) test. An indirect immunofluorescence (IIF) test performed by Human Epithelial type 2 (HEp-2) cells as substrate antigen is the most common methods to determine ANA. In this paper we present an automatic HEp-2 specimen system based on a convolutional neural network method able to classify IIF images. The system consists of a module for features extraction based on a pre-trained AlexNet network and a classification phase for the cell-pattern association using six support vector machines and a k-nearest neighbors classifier. The class…
Deep Convolutional Neural Network for HEp-2 fluorescence intensity classification
2019
Indirect ImmunoFluorescence (IIF) assays are recommended as the gold standard method for detection of antinuclear antibodies (ANAs), which are of considerable importance in the diagnosis of autoimmune diseases. Fluorescence intensity analysis is very often complex, and depending on the capabilities of the operator, the association with incorrect classes is statistically easy. In this paper, we present a Convolutional Neural Network (CNN) system to classify positive/negative fluorescence intensity of HEp-2 IIF images, which is important for autoimmune diseases diagnosis. The method uses the best known pre-trained CNNs to extract features and a support vector machine (SVM) classifier for the …
HEp-2 Cell Classification with heterogeneous classes-processes based on K-Nearest Neighbours
2014
We present a scheme for the feature extraction and classification of the fluorescence staining patterns of HEp-2 cells in IIF images. We propose a set of complementary processes specific to each class of patterns to search. Our set of processes consists of preprocessing,features extraction and classification. The choice of methods, features and parameters was performed automatically, using the Mean Class Accuracy (MCA) as a figure of merit. We extract a large number (108) of features able to fully characterize the staining pattern of HEp-2 cells. We propose a classification approach based on two steps: the first step follows the one-against-all(OAA) scheme, while the second step follows the…
Computer-Assisted Classification Patterns in Autoimmune Diagnostics: The AIDA Project.
2016
International audience; Antinuclear antibodies (ANAs) are significant biomarkers in the diagnosis of autoimmune diseases in humans, done by mean of Indirect ImmunoFluorescence (IIF) method, and performed by analyzing patterns and fluorescence intensity. This paper introduces the AIDA Project (autoimmunity: diagnosis assisted by computer) developed in the framework of an Italy-Tunisia cross-border cooperation and its preliminary results. A database of interpreted IIF images is being collected through the exchange of images and double reporting and a Gold Standard database, containing around 1000 double reported images, has been settled. The Gold Standard database is used for optimization of …