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基于深度学习的胃癌病理切片图像分割算法研究学理学学学160301106870·理学学2020的基于深度学习的胃癌病理切片图像分割算法研究的研究的的的理学学2020基于深度学习的胃癌病理切片图像分割算法研究分深度学习学像研究的基癌病理切片的分割的研究基于的胃癌病理切片的分割法法基的的分割的的分割89%MIoU65%法的法的深度学习学图像分割胃癌病理切片理学学2020ResearchonImageSegmentationAlgorithmofGastricCancerPathologicalSlicesBasedonDeepLearningAbstractBasedontheanalysisandapplicationofdeeplearninginmedicalimagerecognitionathomeandabroad,thispaperconductsadetailedstudyonthesegmentationofcancerpathologicalslices,andproposesanautomaticsegmentationmethodofgastriccancerpathologicalslicesbasedonconvolutionalneuralnetworks.Thismethodisbasedonafullconvolutionalneu-ralnetworkandincorporatesapyramidpoolingmodule.Thepyramidpoolingmodelcaneffectivelyimprovethereceptivefieldofthenetwork,anditcanbetteradapttosegmentedobjectsofdifferentsizes.Andachievedagoodsegmentationeffect.Theexperimentalre-sultsshowthattheaverageaccuracyratereaches89%andMIoUreaches65%.Thismethodhasbeengreatlyimprovedcomparedwiththetraditionalmethodsinthepast.Keywords:DeepLearningPyramidPoolingModelMedicalImageSegmentationGas-tricCancerPathologicalSection理学学2020111.1研究.................................11.2.....................................12的32.1..................................32.2算法.....................................42.2.1度算法...........................42.3.....................................43基于PSPNet胃癌病理切片图像分割53.1.................................53.2PSPNet......................................63.2.1ResNet..................................63.2.2.................................83.2.3..