Performance comparison of our method with existing methods in image type identification.

<p>Performance comparison of our method with existing methods in image type identification.</p>

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Bibliographic Details
Main Author: Faqir Gul (20760068) (author)
Other Authors: Mohsin Shah (3144564) (author), Mushtaq Ali (3598514) (author), Lal Hussain (14100502) (author), Touseef Sadiq (20175797) (author), Adeel Ahmed Abbasi (20760071) (author), Mohammad Shahbaz Khan (17140693) (author), Badr S. Alkahtani (20760074) (author)
Published: 2025
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author Faqir Gul (20760068)
author2 Mohsin Shah (3144564)
Mushtaq Ali (3598514)
Lal Hussain (14100502)
Touseef Sadiq (20175797)
Adeel Ahmed Abbasi (20760071)
Mohammad Shahbaz Khan (17140693)
Badr S. Alkahtani (20760074)
author2_role author
author
author
author
author
author
author
author_facet Faqir Gul (20760068)
Mohsin Shah (3144564)
Mushtaq Ali (3598514)
Lal Hussain (14100502)
Touseef Sadiq (20175797)
Adeel Ahmed Abbasi (20760071)
Mohammad Shahbaz Khan (17140693)
Badr S. Alkahtani (20760074)
author_role author
dc.creator.none.fl_str_mv Faqir Gul (20760068)
Mohsin Shah (3144564)
Mushtaq Ali (3598514)
Lal Hussain (14100502)
Touseef Sadiq (20175797)
Adeel Ahmed Abbasi (20760071)
Mohammad Shahbaz Khan (17140693)
Badr S. Alkahtani (20760074)
dc.date.none.fl_str_mv 2025-02-20T18:26:34Z
dc.identifier.none.fl_str_mv 10.1371/journal.pone.0315823.t001
dc.relation.none.fl_str_mv https://figshare.com/articles/dataset/Performance_comparison_of_our_method_with_existing_methods_in_image_type_identification_/28453031
dc.rights.none.fl_str_mv CC BY 4.0
info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Biochemistry
Medicine
Cell Biology
Biotechnology
Science Policy
Space Science
Biological Sciences not elsewhere classified
Information Systems not elsewhere classified
publicly available datasets
performs efficient segmentation
g ., x
including imageclefmed 2013
image type identification
facilitates fast retrieval
panel image types
irregular image layouts
xlink "> multi
significantly enhances sub
represent approximately 50
patient &# 8217
novel hybrid framework
panel images play
irregular medical images
panel image
image retrieval
irregular multi
proposed framework
imageclefmed 2016
hybrid multi
consolidated image
medical images
medical literature
medical diagnostics
images serve
various multi
thorough representation
paper presents
morphological operations
important tools
extracting sub
essential role
ct scans
consolidated multi
component sub
achieving accurate
dc.title.none.fl_str_mv Performance comparison of our method with existing methods in image type identification.
dc.type.none.fl_str_mv Dataset
info:eu-repo/semantics/publishedVersion
dataset
description <p>Performance comparison of our method with existing methods in image type identification.</p>
eu_rights_str_mv openAccess
id Manara_1f44cf8a2deebfc2fc518297db996bb2
identifier_str_mv 10.1371/journal.pone.0315823.t001
network_acronym_str Manara
network_name_str ManaraRepo
oai_identifier_str oai:figshare.com:article/28453031
publishDate 2025
repository.mail.fl_str_mv
repository.name.fl_str_mv
repository_id_str
rights_invalid_str_mv CC BY 4.0
spelling Performance comparison of our method with existing methods in image type identification.Faqir Gul (20760068)Mohsin Shah (3144564)Mushtaq Ali (3598514)Lal Hussain (14100502)Touseef Sadiq (20175797)Adeel Ahmed Abbasi (20760071)Mohammad Shahbaz Khan (17140693)Badr S. Alkahtani (20760074)BiochemistryMedicineCell BiologyBiotechnologyScience PolicySpace ScienceBiological Sciences not elsewhere classifiedInformation Systems not elsewhere classifiedpublicly available datasetsperforms efficient segmentationg ., xincluding imageclefmed 2013image type identificationfacilitates fast retrievalpanel image typesirregular image layoutsxlink "> multisignificantly enhances subrepresent approximately 50patient &# 8217novel hybrid frameworkpanel images playirregular medical imagespanel imageimage retrievalirregular multiproposed frameworkimageclefmed 2016hybrid multiconsolidated imagemedical imagesmedical literaturemedical diagnosticsimages servevarious multithorough representationpaper presentsmorphological operationsimportant toolsextracting subessential rolect scansconsolidated multicomponent subachieving accurate<p>Performance comparison of our method with existing methods in image type identification.</p>2025-02-20T18:26:34ZDatasetinfo:eu-repo/semantics/publishedVersiondataset10.1371/journal.pone.0315823.t001https://figshare.com/articles/dataset/Performance_comparison_of_our_method_with_existing_methods_in_image_type_identification_/28453031CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/284530312025-02-20T18:26:34Z
spellingShingle Performance comparison of our method with existing methods in image type identification.
Faqir Gul (20760068)
Biochemistry
Medicine
Cell Biology
Biotechnology
Science Policy
Space Science
Biological Sciences not elsewhere classified
Information Systems not elsewhere classified
publicly available datasets
performs efficient segmentation
g ., x
including imageclefmed 2013
image type identification
facilitates fast retrieval
panel image types
irregular image layouts
xlink "> multi
significantly enhances sub
represent approximately 50
patient &# 8217
novel hybrid framework
panel images play
irregular medical images
panel image
image retrieval
irregular multi
proposed framework
imageclefmed 2016
hybrid multi
consolidated image
medical images
medical literature
medical diagnostics
images serve
various multi
thorough representation
paper presents
morphological operations
important tools
extracting sub
essential role
ct scans
consolidated multi
component sub
achieving accurate
status_str publishedVersion
title Performance comparison of our method with existing methods in image type identification.
title_full Performance comparison of our method with existing methods in image type identification.
title_fullStr Performance comparison of our method with existing methods in image type identification.
title_full_unstemmed Performance comparison of our method with existing methods in image type identification.
title_short Performance comparison of our method with existing methods in image type identification.
title_sort Performance comparison of our method with existing methods in image type identification.
topic Biochemistry
Medicine
Cell Biology
Biotechnology
Science Policy
Space Science
Biological Sciences not elsewhere classified
Information Systems not elsewhere classified
publicly available datasets
performs efficient segmentation
g ., x
including imageclefmed 2013
image type identification
facilitates fast retrieval
panel image types
irregular image layouts
xlink "> multi
significantly enhances sub
represent approximately 50
patient &# 8217
novel hybrid framework
panel images play
irregular medical images
panel image
image retrieval
irregular multi
proposed framework
imageclefmed 2016
hybrid multi
consolidated image
medical images
medical literature
medical diagnostics
images serve
various multi
thorough representation
paper presents
morphological operations
important tools
extracting sub
essential role
ct scans
consolidated multi
component sub
achieving accurate