Araştırma Makalesi

An Image Segmentation Method for Wound Healing Assay Images

Cilt: 4 Sayı: 1 30 Haziran 2021
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An Image Segmentation Method for Wound Healing Assay Images

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.

Anahtar Kelimeler

Kaynakça

  1. 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.
  2. 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.
  3. Suarez-Arnedo, Alejandra, et al. "An image J plugin for the high throughput image analysis of in vitro scratch wound healing assays." bioRxiv (2020).
  4. Zordan, Michael D., et al. "A high throughput, interactive imaging, bright‐field wound healing assay." Cytometry Part A 79.3 (2011): 227-232.
  5. 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.
  6. 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.
  7. Huang, Kai, and Robert F. Murphy. "From quantitative microscopy to automated image understanding." Journal of biomedical optics 9.5 (2004): 893-913.
  8. 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.

Ayrıntılar

Birincil Dil

İngilizce

Konular

Bilgisayar Yazılımı, Mühendislik, Elektrik Mühendisliği

Bölüm

Araştırma Makalesi

Yayımlanma Tarihi

30 Haziran 2021

Gönderilme Tarihi

4 Ocak 2021

Kabul Tarihi

5 Nisan 2021

Yayımlandığı Sayı

Yıl 2021 Cilt: 4 Sayı: 1

Kaynak Göster

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. https://doi.org/10.38061/idunas.853356
AMA
1.Erdem YS, 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. doi:10.38061/idunas.853356
Chicago
Erdem, Yusuf Sait, Özden Yalçın Özuysal, Devrim Pesen Okvur, Behçet Töreyin, ve Devrim Ünay. 2021. “An Image Segmentation Method for Wound Healing Assay Images”. Natural and Applied Sciences Journal 4 (1): 30-37. https://doi.org/10.38061/idunas.853356.
EndNote
Erdem YS, Yalçın Özuysal Ö, Pesen Okvur D, Töreyin B, Ünay D (01 Haziran 2021) An Image Segmentation Method for Wound Healing Assay Images. Natural and Applied Sciences Journal 4 1 30–37.
IEEE
[1]Y. S. Erdem, Ö. Yalçın Özuysal, D. Pesen Okvur, B. Töreyin, ve D. Ünay, “An Image Segmentation Method for Wound Healing Assay Images”, IDU Natural and Applied Sciences Journal (IDUNAS), c. 4, sy 1, ss. 30–37, Haz. 2021, doi: 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 (01 Haziran 2021): 30-37. https://doi.org/10.38061/idunas.853356.
JAMA
1.Erdem YS, 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;4:30–37.
MLA
Erdem, Yusuf Sait, vd. “An Image Segmentation Method for Wound Healing Assay Images”. Natural and Applied Sciences Journal, c. 4, sy 1, Haziran 2021, ss. 30-37, doi:10.38061/idunas.853356.
Vancouver
1.Yusuf Sait Erdem, Özden Yalçın Özuysal, Devrim Pesen Okvur, Behçet Töreyin, Devrim Ünay. An Image Segmentation Method for Wound Healing Assay Images. IDU Natural and Applied Sciences Journal (IDUNAS). 01 Haziran 2021;4(1):30-7. doi:10.38061/idunas.853356

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