Araştırma Makalesi
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Yıl 2021, Cilt 4, Sayı 1, 30 - 37, 30.06.2021
https://doi.org/10.38061/idunas.853356

Öz

Kaynakça

  • Matsubayashi, Yutaka, William Razzell, and Paul Martin. "White wave’analysis of epithelial scratch wound healing reveals how cells mobilise back from the leading edge in a myosin-II-dependent fashion." Journal of cell science 124.7 (2011): 1017-1021.
  • Gebäck, Tobias, et al. "TScratch: a novel and simple software tool for automated analysis of monolayer wound healing assays: Short Technical Reports." Biotechniques 46.4 (2009): 265-274.
  • Suarez-Arnedo, Alejandra, et al. "An image J plugin for the high throughput image analysis of in vitro scratch wound healing assays." bioRxiv (2020).
  • Zordan, Michael D., et al. "A high throughput, interactive imaging, bright‐field wound healing assay." Cytometry Part A 79.3 (2011): 227-232.
  • Topman, Gil, Orna Sharabani-Yosef, and Amit Gefen. "A standardized objective method for continuously measuring the kinematics of cultures covering a mechanically damaged site." Medical engineering & physics 34.2 (2012): 225-232.
  • Grada, Ayman, et al. "Research techniques made simple: analysis of collective cell migration using the wound healing assay." Journal of Investigative Dermatology 137.2 (2017): e11-e16.
  • Huang, Kai, and Robert F. Murphy. "From quantitative microscopy to automated image understanding." Journal of biomedical optics 9.5 (2004): 893-913.
  • Garcia, Fossa, Vladimir Fernanda Gaal, and B. de Jesus Marcelo. "PyScratch: an ease of use tool for analysis of Scratch assays." Computer Methods and Programs in Biomedicine (2020): 105476.
  • Milde, Florian, et al. "Cell Image Velocimetry (CIV): boosting the automated quantification of cell migration in wound healing assays." Integrative Biology 4.11 (2012): 1437-1447.
  • Wound healing image segmentation tool: http://dev.mri.cnrs.fr/projects/imagej-macros/wiki/Wound_Healing_Tool
  • Mayalı, Berkay, et al. "Automated Analysis of Wound Healing Microscopy Image Series-A Preliminary Study." 2020 Medical Technologies Congress (TIPTEKNO). IEEE, 2020.
  • Image annotation online tool: https://supervise.ly

An Image Segmentation Method for Wound Healing Assay Images

Yıl 2021, Cilt 4, Sayı 1, 30 - 37, 30.06.2021
https://doi.org/10.38061/idunas.853356

Öz

Wound healing assays are important for molecular biologists to understand the mechanisms of cell migration. For the analysis of wound healing assays, accurate segmentation of the wound front is a necessity. Manual annotation of the wound front is inconvenient since it is time-consuming and annotator-dependent. Thus automated, fast, and robust solutions are required. There are several image processing techniques proposed to fulfill this need. However, requirement for specification of optimal parameters, the need for human intervention, and the lack of high accuracy emerge as the downfalls for most of them. In this study we have proposed a novel method to overcome these difficulties.

Kaynakça

  • Matsubayashi, Yutaka, William Razzell, and Paul Martin. "White wave’analysis of epithelial scratch wound healing reveals how cells mobilise back from the leading edge in a myosin-II-dependent fashion." Journal of cell science 124.7 (2011): 1017-1021.
  • Gebäck, Tobias, et al. "TScratch: a novel and simple software tool for automated analysis of monolayer wound healing assays: Short Technical Reports." Biotechniques 46.4 (2009): 265-274.
  • Suarez-Arnedo, Alejandra, et al. "An image J plugin for the high throughput image analysis of in vitro scratch wound healing assays." bioRxiv (2020).
  • Zordan, Michael D., et al. "A high throughput, interactive imaging, bright‐field wound healing assay." Cytometry Part A 79.3 (2011): 227-232.
  • Topman, Gil, Orna Sharabani-Yosef, and Amit Gefen. "A standardized objective method for continuously measuring the kinematics of cultures covering a mechanically damaged site." Medical engineering & physics 34.2 (2012): 225-232.
  • Grada, Ayman, et al. "Research techniques made simple: analysis of collective cell migration using the wound healing assay." Journal of Investigative Dermatology 137.2 (2017): e11-e16.
  • Huang, Kai, and Robert F. Murphy. "From quantitative microscopy to automated image understanding." Journal of biomedical optics 9.5 (2004): 893-913.
  • Garcia, Fossa, Vladimir Fernanda Gaal, and B. de Jesus Marcelo. "PyScratch: an ease of use tool for analysis of Scratch assays." Computer Methods and Programs in Biomedicine (2020): 105476.
  • Milde, Florian, et al. "Cell Image Velocimetry (CIV): boosting the automated quantification of cell migration in wound healing assays." Integrative Biology 4.11 (2012): 1437-1447.
  • Wound healing image segmentation tool: http://dev.mri.cnrs.fr/projects/imagej-macros/wiki/Wound_Healing_Tool
  • Mayalı, Berkay, et al. "Automated Analysis of Wound Healing Microscopy Image Series-A Preliminary Study." 2020 Medical Technologies Congress (TIPTEKNO). IEEE, 2020.
  • Image annotation online tool: https://supervise.ly

Ayrıntılar

Birincil Dil İngilizce
Konular Mühendislik, Bilgisayar Bilimleri, Bilgi Sistemleri, Mühendislik, Elektrik ve Elektronik
Bölüm Makaleler
Yazarlar

Yusuf Sait ERDEM (Sorumlu Yazar)
İZMİR DEMOKRASİ ÜNİVERSİTESİ
0000-0002-8515-8303
Türkiye


Özden YALÇIN ÖZUYSAL
İZMİR YÜKSEK TEKNOLOJİ ENSTİTÜSÜ, FEN FAKÜLTESİ, MOLEKÜLER BİYOLOJİ VE GENETİK BÖLÜMÜ
0000-0003-0552-368X
Türkiye


Devrim PESEN OKVUR Bu kişi benim
İZMİR YÜKSEK TEKNOLOJİ ENSTİTÜSÜ, FEN FAKÜLTESİ, MOLEKÜLER BİYOLOJİ VE GENETİK BÖLÜMÜ
0000-0001-8333-4193
Türkiye


Behçet TÖREYİN
ISTANBUL TECHNICAL UNIVERSITY, INSTITUTE OF INFORMATICS, DEPARTMENT OF COMPUTATIONAL SCIENCE AND ENGINEERING
0000-0003-4406-2783
Türkiye


Devrim ÜNAY
IZMIR DEMOCRACY UNIVERSITY, FACULTY OF ENGINEERING, DEPARTMENT OF ELECTRICAL AND ELECTRONIC ENGINEERING, DEPARTMENT OF ELECTRICAL AND ELECTRONIC ENGINEERING
0000-0003-3478-7318
Türkiye

Yayımlanma Tarihi 30 Haziran 2021
Yayınlandığı Sayı Yıl 2021, Cilt 4, Sayı 1

Kaynak Göster

Bibtex @araştırma makalesi { idunas853356, journal = {Natural and Applied Sciences Journal}, issn = {2645-9000}, address = {}, publisher = {İzmir Demokrasi Üniversitesi}, year = {2021}, volume = {4}, pages = {30 - 37}, doi = {10.38061/idunas.853356}, title = {An Image Segmentation Method for Wound Healing Assay Images}, key = {cite}, author = {Erdem, Yusuf Sait and Yalçın Özuysal, Özden and Pesen Okvur, Devrim and Töreyin, Behçet and Ünay, Devrim} }
APA Erdem, Y. S. , Yalçın Özuysal, Ö. , Pesen Okvur, D. , Töreyin, B. & Ünay, D. (2021). An Image Segmentation Method for Wound Healing Assay Images . Natural and Applied Sciences Journal , 4 (1) , 30-37 . DOI: 10.38061/idunas.853356
MLA Erdem, Y. S. , Yalçın Özuysal, Ö. , Pesen Okvur, D. , Töreyin, B. , Ünay, D. "An Image Segmentation Method for Wound Healing Assay Images" . Natural and Applied Sciences Journal 4 (2021 ): 30-37 <https://dergipark.org.tr/tr/pub/idunas/issue/63327/853356>
Chicago Erdem, Y. S. , Yalçın Özuysal, Ö. , Pesen Okvur, D. , Töreyin, B. , Ünay, D. "An Image Segmentation Method for Wound Healing Assay Images". Natural and Applied Sciences Journal 4 (2021 ): 30-37
RIS TY - JOUR T1 - An Image Segmentation Method for Wound Healing Assay Images AU - Yusuf Sait Erdem , Özden Yalçın Özuysal , Devrim Pesen Okvur , Behçet Töreyin , Devrim Ünay Y1 - 2021 PY - 2021 N1 - doi: 10.38061/idunas.853356 DO - 10.38061/idunas.853356 T2 - Natural and Applied Sciences Journal JF - Journal JO - JOR SP - 30 EP - 37 VL - 4 IS - 1 SN - 2645-9000- M3 - doi: 10.38061/idunas.853356 UR - https://doi.org/10.38061/idunas.853356 Y2 - 2021 ER -
EndNote %0 Natural and Applied Sciences Journal An Image Segmentation Method for Wound Healing Assay Images %A Yusuf Sait Erdem , Özden Yalçın Özuysal , Devrim Pesen Okvur , Behçet Töreyin , Devrim Ünay %T An Image Segmentation Method for Wound Healing Assay Images %D 2021 %J Natural and Applied Sciences Journal %P 2645-9000- %V 4 %N 1 %R doi: 10.38061/idunas.853356 %U 10.38061/idunas.853356
ISNAD Erdem, Yusuf Sait , Yalçın Özuysal, Özden , Pesen Okvur, Devrim , Töreyin, Behçet , Ünay, Devrim . "An Image Segmentation Method for Wound Healing Assay Images". Natural and Applied Sciences Journal 4 / 1 (Haziran 2021): 30-37 . https://doi.org/10.38061/idunas.853356
AMA Erdem Y. S. , Yalçın Özuysal Ö. , Pesen Okvur D. , Töreyin B. , Ünay D. An Image Segmentation Method for Wound Healing Assay Images. IDU Natural and Applied Sciences Journal (IDUNAS). 2021; 4(1): 30-37.
Vancouver Erdem Y. S. , Yalçın Özuysal Ö. , Pesen Okvur D. , Töreyin B. , Ünay D. An Image Segmentation Method for Wound Healing Assay Images. Natural and Applied Sciences Journal. 2021; 4(1): 30-37.
IEEE Y. S. Erdem , Ö. Yalçın Özuysal , D. Pesen Okvur , B. Töreyin ve D. Ünay , "An Image Segmentation Method for Wound Healing Assay Images", Natural and Applied Sciences Journal, c. 4, sayı. 1, ss. 30-37, Haz. 2021, doi:10.38061/idunas.853356