1. Identity statement | |
Reference Type | Conference Paper (Conference Proceedings) |
Site | sibgrapi.sid.inpe.br |
Identifier | 8JMKD3MGPEW34M/4BFC5SP |
Repository | sid.inpe.br/sibgrapi/2024/06.14.00.26 |
Last Update | 2024:06.14.00.27.03 (UTC) gumartinslopes@gmail.com |
Metadata Repository | sid.inpe.br/sibgrapi/2024/06.14.00.27 |
Metadata Last Update | 2024:06.21.01.38.42 (UTC) administrator |
Citation Key | CostaRoFoJrSoGu:2023:SiObDe |
Title | Single-Shot Object Detection and Supervised Image Segmentation for Analysing Cell Images Obtainedby Immunohistochemistry |
Short Title | Single-Shot Object Detection and Supervised Image Segmentation for Analysing Cell Images Obtainedby Immunohistochemistry |
Format | On-line |
Year | 2023 |
Access Date | 2024, Sep. 08 |
Number of Files | 1 |
Size | 1612 KiB |
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2. Context | |
Author | 1 Costa, Gustavo Martins Lopes da 2 Rodrigues, Anna P. C. 3 Fonseca, Gabriel Barbosa da 4 Jr, Zenilton K. G. do Patrocínio 5 Souto, Giovanna Ribeiro 6 Guimarăes, Silvio Jamil F. |
Affiliation | 1 PUC Minas 2 PUC Minas 3 PUC Minas 4 PUC Minas 5 PUC Minas 6 PUC Minas |
Editor | Clua, Esteban Walter Gonzalez Körting, Thales Sehn Paulovich, Fernando Vieira Feris, Rogerio |
e-Mail Address | gumartinslopes@gmail.com |
Conference Name | Conference on Graphics, Patterns and Images, 36 (SIBGRAPI) |
Conference Location | Rio Grande, RS |
Date | Nov. 06-09, 2023 |
Book Title | Proceedings |
Tertiary Type | Work in Progress |
History (UTC) | 2024-06-14 00:27:08 :: gumartinslopes@gmail.com -> administrator :: 2024-06-21 01:38:42 :: administrator -> :: 2023 |
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3. Content and structure | |
Is the master or a copy? | is the master |
Content Stage | completed |
Transferable | 1 |
Keywords | Image Segmentation Cell Detection Computer Vision Machine Learning Immunohistochemistry |
Abstract | Analyzing cell images and identifying them correctly is a fundamental task in the immunohistochemical exam. In this paper we propose a novel method to segment FoxP3+ Regulatory T cells (Treg) images automatically, in order to assist healthcare professionals in the task of identifying and counting potentially cancerous cells. The proposed method relies on combining an object detection network, which is tailor-made for microscopy images, with a marker-based image segmentation method to produce the final segmentation, while requiring only a 50x50 training patch to do so. Our pipeline consists on predicting the location of the cells, applying morphological operations on the prediction weights to transform them into markers, and finally using the segmentation method iDISF to generate high quality segmentations. We also propose a new FoxP3+ Treg cells dataset containing 10 high resolution images, with a qualitative and quantitative analysis of our segmentation methods for this dataset. |
Arrangement | urlib.net > SDLA > Fonds > SIBGRAPI 2023 > Single-Shot Object Detection and Supervised Image Segmentation for Analysing Cell Images Obtainedby Immunohistochemistry |
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://sibgrapi.sid.inpe.br/ibi/8JMKD3MGPEW34M/4BFC5SP |
zipped data URL | http://sibgrapi.sid.inpe.br/zip/8JMKD3MGPEW34M/4BFC5SP |
Language | en |
Target File | Single-Shot Object Detection and Supervised ImageSegmentation for Analysing Cell Images Obtainedby Immunohistochemistry.pdf |
User Group | gumartinslopes@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/4BG6FTP |
Citing Item List | sid.inpe.br/sibgrapi/2024/06.18.21.17 19 |
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 holdercode isbn issn label lineage mark nextedition notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project publisher publisheraddress readergroup readpermission resumeid rightsholder schedulinginformation secondarydate secondarykey secondarymark secondarytype serieseditor session sponsor subject tertiarymark type url versiontype volume |
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