convolutional networks can learn to generate affinity graphs for image segmentationnew

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1、LETTERCommunicatedbyDmitriChklovskiiConvolutionalNetworksCanLearntoGenerateAffinityGraphsforImageSegmentationSrinivasC.Turaga∗sturaga@mit.eduDepartmentofBrainandCognitiveSciences,MassachusettsInstituteofTechnology,Cambridge,MA02139,U.S.A.JosephF.Murray∗jfmu

2、rray@jfmurray.orgDepartmentofBrainandCognitiveSciences,MassachusettsInstituteofTechnology,HowardHughesMedicalInstitute,Cambridge,MA02139,U.S.A.VirenJainviren@mit.eduDepartmentofBrainandCognitiveSciences,MassachusettsInstituteofTechnology,Cambridge,MA02139,

3、U.S.A.FabianRothfabian.roth@gmail.comDepartmentofBrainandCognitiveSciences,MassachusettsInstituteofTechnology,HowardHughesMedicalInstitute,Cambridge,MA02139,U.S.A.MoritzHelmstaedterMoritz.Helmstaedter@mpimf-heidelberg.mpg.deKevinBriggmanKevin.Briggman@mpim

4、f-heidelberg.mpg.deWinfriedDenkWinfried.Denk@mpimf-heidelberg.mpg.deMax-PlanckInstituteforMedicalResearch,D-69120,Heidelberg,GermanyH.SebastianSeungseung@mit.eduDepartmentsofBrainandCognitiveSciencesandPhysics,MassachusettsInstituteofTechnology,HowardHughe

5、sMedicalInstitute,Cambridge,MA02139,U.S.A.Manyimagesegmentationalgorithmsfirstgenerateanaffinitygraphandthenpartitionit.Wepresentamachinelearningapproachtocomputing∗Theseauthorscontributedequallytothewritingofthisletter.NeuralComputation22,511–538(2010)C200

6、9MassachusettsInstituteofTechnology512S.Turagaetal.anaffinitygraphusingaconvolutionalnetwork(CN)trainedusinggroundtruthprovidedbyhumanexperts.TheCNaffinitygraphcanbepairedwithanystandardpartitioningalgorithmandimprovessegmenta-tionaccuracysignificantlycompare

7、dtostandardhand-designedaffinityfunctions.Weapplyouralgorithmtothechallenging3Dsegmentationproblemofreconstructingneuronalprocessesfromvolumetricelectronmicroscopy(EM)andshowthatweareabletolearnagoodaffinitygraphdirectlyfromtherawEMimages.Further,weshowthato

8、uraffinitygraphim-provesthesegmentationaccuracyofbothsimpleandsophisticatedgraphpartitioningalgorithms.Incontrasttopreviouswork,wedonotrelyonpriorknowledgeintheformofhand-designedimagefeaturesorimagepreprocess