_version_ 1852019488591970304
author Seok Jin Bang (13028202)
author2 Yong-Tae Kim (249037)
Young Jae Kim (8098697)
Kwang Gi Kim (10654900)
author2_role author
author
author
author_facet Seok Jin Bang (13028202)
Yong-Tae Kim (249037)
Young Jae Kim (8098697)
Kwang Gi Kim (10654900)
author_role author
dc.creator.none.fl_str_mv Seok Jin Bang (13028202)
Yong-Tae Kim (249037)
Young Jae Kim (8098697)
Kwang Gi Kim (10654900)
dc.date.none.fl_str_mv 2025-06-09T17:37:35Z
dc.identifier.none.fl_str_mv 10.1371/journal.pone.0324021.g004
dc.relation.none.fl_str_mv https://figshare.com/articles/figure/Models_Architecture_/29271978
dc.rights.none.fl_str_mv CC BY 4.0
info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Medicine
Space Science
Environmental Sciences not elsewhere classified
Biological Sciences not elsewhere classified
Information Systems not elsewhere classified
second leading cause
fully connected network
dice similarity coefficient
validated using five
fcn model exhibited
xlink "> stroke
ischemic stroke collected
constructed using data
net model demonstrated
artificial intelligence models
apparent diffusion coefficient
lesion segmentation performance
dsc ), accuracy
adc images based
lesion segmentation
fcn ),
conducted using
image data
evaluated based
adc based
stroke diagnosis
weighted imaging
utilizing images
training models
trained models
retrospective design
future research
fold cross
different b
deaths worldwide
comparing diffusion
comparative analysis
adc images
360 patients
dc.title.none.fl_str_mv Models Architecture.
dc.type.none.fl_str_mv Image
Figure
info:eu-repo/semantics/publishedVersion
image
description <p>(a) Architecture of the model used in the experiment fully connencted network (FCN) architecture. (b) U-Net architecture.</p>
eu_rights_str_mv openAccess
id Manara_bddc8db6dc0ac57726d2e5fa39c19009
identifier_str_mv 10.1371/journal.pone.0324021.g004
network_acronym_str Manara
network_name_str ManaraRepo
oai_identifier_str oai:figshare.com:article/29271978
publishDate 2025
repository.mail.fl_str_mv
repository.name.fl_str_mv
repository_id_str
rights_invalid_str_mv CC BY 4.0
spelling Models Architecture.Seok Jin Bang (13028202)Yong-Tae Kim (249037)Young Jae Kim (8098697)Kwang Gi Kim (10654900)MedicineSpace ScienceEnvironmental Sciences not elsewhere classifiedBiological Sciences not elsewhere classifiedInformation Systems not elsewhere classifiedsecond leading causefully connected networkdice similarity coefficientvalidated using fivefcn model exhibitedxlink "> strokeischemic stroke collectedconstructed using datanet model demonstratedartificial intelligence modelsapparent diffusion coefficientlesion segmentation performancedsc ), accuracyadc images basedlesion segmentationfcn ),conducted usingimage dataevaluated basedadc basedstroke diagnosisweighted imagingutilizing imagestraining modelstrained modelsretrospective designfuture researchfold crossdifferent bdeaths worldwidecomparing diffusioncomparative analysisadc images360 patients<p>(a) Architecture of the model used in the experiment fully connencted network (FCN) architecture. (b) U-Net architecture.</p>2025-06-09T17:37:35ZImageFigureinfo:eu-repo/semantics/publishedVersionimage10.1371/journal.pone.0324021.g004https://figshare.com/articles/figure/Models_Architecture_/29271978CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/292719782025-06-09T17:37:35Z
spellingShingle Models Architecture.
Seok Jin Bang (13028202)
Medicine
Space Science
Environmental Sciences not elsewhere classified
Biological Sciences not elsewhere classified
Information Systems not elsewhere classified
second leading cause
fully connected network
dice similarity coefficient
validated using five
fcn model exhibited
xlink "> stroke
ischemic stroke collected
constructed using data
net model demonstrated
artificial intelligence models
apparent diffusion coefficient
lesion segmentation performance
dsc ), accuracy
adc images based
lesion segmentation
fcn ),
conducted using
image data
evaluated based
adc based
stroke diagnosis
weighted imaging
utilizing images
training models
trained models
retrospective design
future research
fold cross
different b
deaths worldwide
comparing diffusion
comparative analysis
adc images
360 patients
status_str publishedVersion
title Models Architecture.
title_full Models Architecture.
title_fullStr Models Architecture.
title_full_unstemmed Models Architecture.
title_short Models Architecture.
title_sort Models Architecture.
topic Medicine
Space Science
Environmental Sciences not elsewhere classified
Biological Sciences not elsewhere classified
Information Systems not elsewhere classified
second leading cause
fully connected network
dice similarity coefficient
validated using five
fcn model exhibited
xlink "> stroke
ischemic stroke collected
constructed using data
net model demonstrated
artificial intelligence models
apparent diffusion coefficient
lesion segmentation performance
dsc ), accuracy
adc images based
lesion segmentation
fcn ),
conducted using
image data
evaluated based
adc based
stroke diagnosis
weighted imaging
utilizing images
training models
trained models
retrospective design
future research
fold cross
different b
deaths worldwide
comparing diffusion
comparative analysis
adc images
360 patients