简介：Severalfeaturesofretinalvesselscanbeusedtomonitortheprogressionofdiseases.Changesinvascularstructures,forexample,vesselcaliber,branchingangle,andtortuosity,areportentsofmanydiseasessuchasdiabeticretinopathyandarterialhypertension.Thispaperproposesanautomaticretinalvesselsegmentationmethodbasedonmorphologicalclosingandmulti-scalelinedetection.First,anilluminationcorrectionisperformedonthegreenbandretinalimage.Next,themorphologicalclosingandsubtractionprocessingareappliedtoobtainthecruderetinalvesselimage.Then,themulti-scalelinedetectionisusedtofinethevesselimage.Finally,thebinaryvasculatureisextractedbytheOtsualgorithm.Inthispaper,forimprovingthedrawbacksofmulti-scalelinedetection,onlythelinedetectorsat4scalesareused.Theexperimentalresultsshowthattheaccuracyis0.939forDRIVE(digitalretinalimagesforvesselextraction)retinaldatabase,whichismuchbetterthanothermethods.