Utilization Of Convolutional Neural Networks For Segmentation Of Mouse Embryos Cartilaginous Tissue In Micro-Ct Data

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but.event.date27.04.2021cs
but.event.titleSTUDENT EEICT 2021cs
dc.contributor.authorPoláková, Veronika
dc.date.accessioned2023-01-06T10:05:43Z
dc.date.available2023-01-06T10:05:43Z
dc.date.issued2021cs
dc.description.abstractAutomatic segmentation of the biological structures in micro-CT data is still a challengesince the object of interest (craniofacial cartilage in our case) is commonly not characterized by uniquevoxel intensity or sharp borders. In recent years, convolutional neural networks (CNNs) have becomeexceedingly popular in many areas of computer vision. Specifically, for biomedical image segmentationproblems, U-Net architecture is widely used. However, in case of micro-CT data, there isa question whether 3D CNN would not be more beneficial. This paper introduces CNN architecturebased on V-Net as well as the methodology for data preprocessing and postprocessing. The baselinearchitecture was further optimized using advanced techniques such as Atrous Spatial Pyramid Pooling(ASPP) module, Scaled Exponential Linear Unit (SELU) activation function, multi-output supervisionand Dense blocks. For network learning, modern approaches were used including learning ratewarmup or AdamW optimizer. Even though the 3D CNN do not outperform U-Net regarding the craniofacialcartilage segmentation, the optimization raises the median of Dice coefficient from 69.74 %to 80.01 %. Therefore, utilizing these advanced techniques is highly encouraged as they can be easilyadded to any U-Net-like architecture and may remarkably improve the results.en
dc.formattextcs
dc.format.extent106-110cs
dc.format.mimetypeapplication/pdfen
dc.identifier.citationProceedings II of the 27st Conference STUDENT EEICT 2021: Selected Papers. s. 106-110. ISBN 978-80-214-5943-4cs
dc.identifier.doi10.13164/eeict.2021.106
dc.identifier.isbn978-80-214-5943-4
dc.identifier.urihttp://hdl.handle.net/11012/200821
dc.language.isoencs
dc.publisherVysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologiícs
dc.relation.ispartofProceedings II of the 27st Conference STUDENT EEICT 2021: Selected papersen
dc.relation.urihttps://conf.feec.vutbr.cz/eeict/index/pages/view/ke_stazenics
dc.rights© Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologiícs
dc.rights.accessopenAccessen
dc.subjectCNNen
dc.subjectmicro-CTen
dc.subjectimage segmentationen
dc.subjectcartilaginous tissueen
dc.subjectV-Neten
dc.titleUtilization Of Convolutional Neural Networks For Segmentation Of Mouse Embryos Cartilaginous Tissue In Micro-Ct Dataen
dc.type.driverconferenceObjecten
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
eprints.affiliatedInstitution.departmentFakulta elektrotechniky a komunikačních technologiícs
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