Wound healing problem requires the analysis of tens of images from different microscopic systems. We describe a set of semi-automatic algorithms to analyze a variety of microscopy images used to study the wound healing process. The proposed suite, beside the phase contrast images, allows analyzing fluorescent microscopy images, inverted light microscopy images at different magnification and staining methods, or images obtained by scanning electron microscopy. The proposed software is designed in Matlab®. It is suggested to integrate it into the CellProfilerTM software, thus introducing new functionalities without losing the CellProfiler existing capabilities. The approach is efficient, easy-to-use, and enables biologists to comprehensively and quantitatively address many questions of the wound healing problem.

Numerical Methods for the Semi-Automatic Analysis of Multimodal Wound Healing Images

PLACIDI, GIUSEPPE;CIFONE, MARIA GRAZIA;CINQUE, BENEDETTA;GIULIANI, Maurizio;MACCHIARELLI, GUIDO;
2010-01-01

Abstract

Wound healing problem requires the analysis of tens of images from different microscopic systems. We describe a set of semi-automatic algorithms to analyze a variety of microscopy images used to study the wound healing process. The proposed suite, beside the phase contrast images, allows analyzing fluorescent microscopy images, inverted light microscopy images at different magnification and staining methods, or images obtained by scanning electron microscopy. The proposed software is designed in Matlab®. It is suggested to integrate it into the CellProfilerTM software, thus introducing new functionalities without losing the CellProfiler existing capabilities. The approach is efficient, easy-to-use, and enables biologists to comprehensively and quantitatively address many questions of the wound healing problem.
2010
978-3-642-12711-3
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11697/2719
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