Med Biol Eng Comput - Centromere and cytoplasmic staining pattern recognition: a local approach.

Tópicos

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Resumo

Autoimmune diseases are very serious and also invalidating illnesses. The benchmark procedure for their diagnosis is the indirect immunofluorescence (IIF) assay performed on the HEp-2 substrate. Medical doctors first determine the fluorescence intensity exhibited by HEp-2 wells and then report the staining pattern. Despite its pivotal role, IIF is affected by inter- and intra-laboratory variabilities demanding for the development of computer-aided-diagnosis tools supporting medical doctor decisions. With reference to staining pattern recognition, state-of-the-art approaches recognize five main patterns characterized by well-defined cell edges. These approaches are based on cell segmentation, a task that recent work suggests to be harder than the classification itself. In this paper, we extend the panel of detectable HEp-2 staining patterns, introducing the recognition of centromere and cytoplasmic patterns, which have a high specific match with certain autoimmune diseases, from other stainings. Since image segmentation algorithms fail on these samples, we developed a classification system integrating local descriptors and the bag of visual word approach, which represents image contents without the burden of segmentation. We tested our approach on a large dataset of HEp-2 images with high variability in both fluorescence intensity and staining patterns correctly recognizing the 97.12?% of samples. The system has also been validated in a daily routine fashion on 108 consecutive IIF analyses of hospital outpatients and inpatients, achieving an accuracy rate of 97.22?%.

Resumo Limpo

autoimmun diseas serious also invalid ill benchmark procedur diagnosi indirect immunofluoresc iif assay perform hep substrat medic doctor first determin fluoresc intens exhibit hep well report stain pattern despit pivot role iif affect inter intralaboratori variabl demand develop computeraideddiagnosi tool support medic doctor decis refer stain pattern recognit stateoftheart approach recogn five main pattern character welldefin cell edg approach base cell segment task recent work suggest harder classif paper extend panel detect hep stain pattern introduc recognit centromer cytoplasm pattern high specif match certain autoimmun diseas stain sinc imag segment algorithm fail sampl develop classif system integr local descriptor bag visual word approach repres imag content without burden segment test approach larg dataset hep imag high variabl fluoresc intens stain pattern correct recogn sampl system also valid daili routin fashion consecut iif analys hospit outpati inpati achiev accuraci rate

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