KaydedilenlerDerginizi ekleyin

Dergiler / Natural and Applied Sciences Journal / 2026 / Cilt: 4 Sayı: 1

An Image Segmentation Method for Wound Healing Assay Images

Yusuf Sait Erdem(İZMİR DEMOKRASİ ÜNİVERSİTESİ)0000-0002-8515-8303
Özden Yalçın Özuysal(İZMİR YÜKSEK TEKNOLOJİ ENSTİTÜSÜ, FEN FAKÜLTESİ, MOLEKÜLER BİYOLOJİ VE GENETİK BÖLÜMÜ)0000-0003-0552-368X
Devrim Pesen Okvur(İZMİR YÜKSEK TEKNOLOJİ ENSTİTÜSÜ, FEN FAKÜLTESİ, MOLEKÜLER BİYOLOJİ VE GENETİK BÖLÜMÜ)0000-0001-8333-4193
Behçet Töreyin(ISTANBUL TECHNICAL UNIVERSITY, INSTITUTE OF INFORMATICS, DEPARTMENT OF COMPUTATIONAL SCIENCE AND ENGINEERING)0000-0003-4406-2783
Devrim Ünay(IZMIR DEMOCRACY UNIVERSITY, FACULTY OF ENGINEERING, DEPARTMENT OF ELECTRICAL AND ELECTRONIC ENGINEERING, DEPARTMENT OF ELECTRICAL AND ELECTRONIC ENGINEERING)0000-0003-3478-7318
Sayfa
30–37
Yayın Tarihi
2021-06-30
🏛️Bu makalenin bibliyografik verileri ve tam metin bağlantısı DergiPark üzerinden sağlanmıştır.
DergiPark Kaydı ↗
✨

Yapay Zeka Hızlı Bakış & Çıkarımlar

AI Insight
⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

In this study we have proposed a novel method to overcome these difficulties.

📌 3 Maddede Bu Makale

🎯
Amaç & Hipotez:Wound healing assays are important for molecular biologists to understand the mechanisms of cell migration.
📊
Temel Bulgular & Veri:For the analysis of wound healing assays, accurate segmentation of the wound front is a necessity.
💡
Sonuç & Katkı:In this study we have proposed a novel method to overcome these difficulties.
🔬Tür:Araştırma Makalesi
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Image segmentation · quantification · wound healing assay

Abstract

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.

🔖

Bu Makaleye Atıf Yap

Erdem, Y. S., Özuysal, Ö. Y., Okvur, D. P., Töreyin, B., Ünay, D. (2021). An Image Segmentation Method for Wound Healing Assay Images. Natural and Applied Sciences Journal, Cilt: 4 Sayı: 1, 30–37. https://doi.org/10.38061/idunas.853356

📄 Tam Metin PDF Okuyucu

📄

PDF görüntüleyici hazırlanıyor...

Kaynakça (12)

  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.
  9. 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.
  10. Wound healing image segmentation tool: http://dev.mri.cnrs.fr/projects/imagej-macros/wiki/Wound_Healing_Tool
  11. Mayalı, Berkay, et al. "Automated Analysis of Wound Healing Microscopy Image Series-A Preliminary Study." 2020 Medical Technologies Congress (TIPTEKNO). IEEE, 2020.
  12. Image annotation online tool: https://supervise.ly