Automated Analysis of Wound Healing Microscopy Image Series - A Preliminary Study

Berkay Mayalıve, Orkun Şaylığ, Ö. Y. Özuysal, D. P. Okvur, B. U. Töreyin, D. Ünay
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引用次数: 2

Abstract

Collective cell analysis from microscopy image series is important for wound healing research. Computer-based automation of such analyses may help in rapid acquisition of reliable and reproducible results. In this study phase-contrast optical microscopy image series of an in-vitro wound healing essay is manually delineated by two experts and its analysis is realized, traditional image processing and deep learning based approaches for automated segmentation of wound area are developed and their performance comparisons are carried out.
伤口愈合显微图像系列的自动分析-初步研究
显微图像序列的集体细胞分析对伤口愈合研究具有重要意义。以计算机为基础的自动化分析有助于快速获得可靠和可重复的结果。在本研究中,两位专家手动描绘了体外伤口愈合文章的相对比光学显微镜图像系列并实现了其分析,开发了传统图像处理和基于深度学习的伤口区域自动分割方法,并对其性能进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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