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POLÁKOVÁ, V.
Original Title
UTILIZATION OF CONVOLUTIONAL NEURAL NETWORKS FOR SEGMENTATION OF MOUSE EMBRYOS CARTILAGINOUS TISSUE IN MICRO-CTDATA
Type
conference paper
Language
English
Original Abstract
Automaticsegmentationofthebiologicalstructuresinmicro-CTdataisstillachallenge sincetheobjectofinterest(craniofacialcartilageinourcase)iscommonlynotcharacterizedbyunique voxelintensityorsharpborders.Inrecentyears,convolutionalneuralnetworks(CNNs)havebecome exceedinglypopularinmanyareasofcomputervision.Specifically,forbiomedicalimagesegmentationproblems,U-Netarchitectureiswidelyused.However,incaseofmicro-CTdata,thereis aquestionwhether3DCNNwouldnotbemorebeneficial.ThispaperintroducesCNNarchitecture basedonV-Netaswellasthemethodologyfordatapreprocessingandpostprocessing.Thebaseline architecturewasfurtheroptimizedusingadvancedtechniquessuchasAtrousSpatialPyramidPooling (ASPP)module,ScaledExponentialLinearUnit(SELU)activationfunction,multi-outputsupervisionandDenseblocks.Fornetworklearning,modernapproacheswereusedincludinglearningrate warmuporAdamWoptimizer.Eventhoughthe3DCNNdonotoutperformU-Netregardingthecraniofacialcartilagesegmentation,theoptimizationraisesthemedianofDicecoefficientfrom69.74% to80.01%.Therefore,utilizingtheseadvancedtechniquesishighlyencouragedastheycanbeeasily addedtoanyU-Net-likearchitectureandmayremarkablyimprovetheresults.
Keywords
CNN,micro-CT,imagesegmentation,cartilaginoustissue,V-Net
Authors
Released
27. 4. 2021
Publisher
Brno University of Technology, Faculty of Electrical Engineering and Communication
Location
Brno
ISBN
978-80-214-5943-4
Book
PROCEEDINGS II OF THE 27TH STUDENT EEICT 2021 selected papers
Edition
1
Pages from
106
Pages to
110
Pages count
5
URL
https://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2021_sbornik_2_v3_DOI.pdf
BibTex
@inproceedings{BUT183914, author="Veronika {Poláková}", title="UTILIZATION OF CONVOLUTIONAL NEURAL NETWORKS FOR SEGMENTATION OF MOUSE EMBRYOS CARTILAGINOUS TISSUE IN MICRO-CTDATA", booktitle="PROCEEDINGS II OF THE 27TH STUDENT EEICT 2021 selected papers", year="2021", series="1", pages="106--110", publisher="Brno University of Technology, Faculty of Electrical Engineering and Communication", address="Brno", doi="10.13164/eeict.2021.106", isbn="978-80-214-5943-4", url="https://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2021_sbornik_2_v3_DOI.pdf" }