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基于异常检测的尿沉渣图像分割.docx

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基于异常检测的尿沉渣图像分割 Introduction Urinarysediment(urinesediment)isamicroscopicexaminationoftheurine,whichisusedtodetectvariousdiseases.Urinesedimentincludesredbloodcells,whitebloodcells,epithelialcells,casts,crystals,andothersubstances.Inordertoaccuratelydiagnoseurinarysystemdiseases,doctorsuseurinarysedimentanalysistoclassifyandcountdifferentcelltypesinurinesamples.However,manualanalysisofurinesedimentisatime-consumingandlaborioustask,anditmayresultinlowaccuracyandpoorreproducibility.Therefore,developinganautomaticandaccuratemethodforurinesedimentanalysisisnecessary. Imagesegmentationisacriticalstepintheautomaticanalysisofurinesediment.Imagesegmentationreferstotheprocessofpartitioninganimageintoseveralregionswithdifferentproperties.Itisanessentialstepinimageprocessing,computervision,andpatternrecognition.Inthecontextofurinesedimentanalysis,imagesegmentationcanseparatedifferenttypesofcellsandparticlesinurinesediment,anditcanprovidemoreaccurateandreliableresults. However,segmentationofurinesedimentimagesisachallengingtaskduetovariousfactors,suchasthelowcontrast,noise,andheterogeneityofcellshapesandsizes.Inrecentyears,manyresearchershaveproposeddifferentmethodsforurinarysedimentimagesegmentation.Amongthesemethods,abnormaldetection-basedmethodshaveattractedconsiderableattentionduetotheirexcellentperformance. Inthispaper,weproposeanabnormaldetection-basedmethodforurinesedimentimagesegmentation.Theproposedmethodcaneffectivelyovercomethedifficultiesinurinarysedimentimagesegmentationandprovidemoreaccurateresults. Methodology TheoverallframeworkoftheproposedmethodisshowninFigure1.Theproposedmethodconsistsofthreemainsteps,asfollows: Step1:Preprocessing Thefirststepisimagepreprocessing,whichiscriticalforenhancingimagequalityandimprovingtheaccuracyofsegmentation.Inthisstep,weusemedianfilteringtoremovesalt-and-peppernoiseintheinputimage.Then,weapplyhistogramequalizationtoimprovethecontrastoftheimage.Finally,weperformmorphologicaloperations,suchaserosionanddilation,toremovesmallobject