1. Identity statement | |
Reference Type | Conference Paper (Conference Proceedings) |
Site | sibgrapi.sid.inpe.br |
Holder Code | ibi 8JMKD3MGPEW34M/46T9EHH |
Identifier | 8JMKD3MGPEW34M/45E4SE5 |
Repository | sid.inpe.br/sibgrapi/2021/09.13.18.23 |
Last Update | 2021:09.13.18.23.57 (UTC) administrator |
Metadata Repository | sid.inpe.br/sibgrapi/2021/09.13.18.23.57 |
Metadata Last Update | 2022:09.10.00.16.17 (UTC) administrator |
Citation Key | Santos:2021:SeSeSk |
Title | Semi-automatic Segmentation of Skin Lesions based on Superpixels and Hybrid Texture Information |
Format | On-line |
Year | 2021 |
Access Date | 2024, May 06 |
Number of Files | 1 |
Size | 20009 KiB |
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2. Context | |
Author | Santos, Elineide Silva dos |
Affiliation | Federal University of Piauí |
Editor | Paiva, Afonso Menotti, David Baranoski, Gladimir V. G. Proença, Hugo Pedro Junior, Antonio Lopes Apolinario Papa, João Paulo Pagliosa, Paulo dos Santos, Thiago Oliveira e Sá, Asla Medeiros da Silveira, Thiago Lopes Trugillo Brazil, Emilio Vital Ponti, Moacir A. Fernandes, Leandro A. F. Avila, Sandra |
e-Mail Address | elineide.silva.inf@gmail.com |
Conference Name | Conference on Graphics, Patterns and Images, 34 (SIBGRAPI) |
Conference Location | Gramado, RS, Brazil (virtual) |
Date | 18-22 Oct. 2021 |
Publisher | Sociedade Brasileira de Computação |
Publisher City | Porto Alegre |
Book Title | Proceedings |
Tertiary Type | Master's or Doctoral Work |
History (UTC) | 2021-09-13 18:23:57 :: elineide.silva.inf@gmail.com -> administrator :: 2022-09-10 00:16:17 :: administrator -> :: 2021 |
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3. Content and structure | |
Is the master or a copy? | is the master |
Content Stage | completed |
Transferable | 1 |
Keywords | Dermatoscopic image segmentation. Computer-aided diagnosis. Skin lesion. Texture information |
Abstract | This article exposes a semi-automatic method with the potential to aid the doctor while supervising the progression of skin lesions. The proposed methodology pre-segments skin lesions using the SLIC0 algorithm for the generation of superpixels. Following this, each superpixel is represented using a descriptor constructed of a mix from GLCM and Tamura texture features. The feature's gain ratios were utilized to choose the data applied in the semi-supervised clustering algorithm Seeded Fuzzy C-means. This algorithm uses certain specialist-marked regions to group the superpixels into lesion or background regions. Finally, the segmented image undergoes a post-processing step to eliminate sharp edges. The experiments were performed on a total of 3974 images. We used the 2995 images from PH2, DermIS and ISIC 2018 datasets to establish our method's specifications and the 979 images from ISIC 2016 and ISIC 2017 datasets for performance analysis. Our experiments demonstrate that by manually identifying a few percentages of the generated superpixels, the proposed approach reaches an average accuracy of 95.97%, thus giving a superior performance to the techniques presented in the literature. Even though the proposed method requires physicians' intervention, they can obtain segmentation results similar to manual segmentation from a significantly less time-consuming task. |
Arrangement | urlib.net > SDLA > Fonds > SIBGRAPI 2021 > Semi-automatic Segmentation of... |
doc Directory Content | access |
source Directory Content | there are no files |
agreement Directory Content | |
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4. Conditions of access and use | |
data URL | http://urlib.net/ibi/8JMKD3MGPEW34M/45E4SE5 |
zipped data URL | http://urlib.net/zip/8JMKD3MGPEW34M/45E4SE5 |
Language | en |
Target File | WTD___SIBGRAPI_2021___Elineide.pdf |
User Group | elineide.silva.inf@gmail.com |
Visibility | shown |
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5. Allied materials | |
Mirror Repository | sid.inpe.br/banon/2001/03.30.15.38.24 |
Next Higher Units | 8JMKD3MGPEW34M/45PQ3RS |
Citing Item List | sid.inpe.br/sibgrapi/2021/11.12.11.46 3 |
Host Collection | sid.inpe.br/banon/2001/03.30.15.38 |
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6. Notes | |
Empty Fields | archivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination documentstage doi edition electronicmailaddress group isbn issn label lineage mark nextedition notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project readergroup readpermission resumeid rightsholder schedulinginformation secondarydate secondarykey secondarymark secondarytype serieseditor session shorttitle sponsor subject tertiarymark type url versiontype volume |
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