Share Email Print
cover

Proceedings Paper

Three-dimensional volume analysis of vasculature in engineered tissues
Author(s): Mohammed YousefHussien; Kelley Garvin; Diane Dalecki; Eli Saber; María Helguera
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

Three-dimensional textural and volumetric image analysis holds great potential in understanding the image data produced by multi-photon microscopy. In this paper, an algorithm that quantitatively analyzes the texture and the morphology of vasculature in engineered tissues is proposed. The investigated 3D artificial tissues consist of Human Umbilical Vein Endothelial Cells (HUVEC) embedded in collagen exposed to two regimes of ultrasound standing wave fields under different pressure conditions. Textural features were evaluated using the normalized Gray-Scale Cooccurrence Matrix (GLCM) combined with Gray-Level Run Length Matrix (GLRLM) analysis. To minimize error resulting from any possible volume rotation and to provide a comprehensive textural analysis, an averaged version of nine GLCM and GLRLM orientations is used. To evaluate volumetric features, an automatic threshold using the gray level mean value is utilized. Results show that our analysis is able to differentiate among the exposed samples, due to morphological changes induced by the standing wave fields. Furthermore, we demonstrate that providing more textural parameters than what is currently being reported in the literature, enhances the quantitative understanding of the heterogeneity of artificial tissues.

Paper Details

Date Published: 4 February 2013
PDF: 11 pages
Proc. SPIE 8654, Visualization and Data Analysis 2013, 86540C (4 February 2013); doi: 10.1117/12.2004765
Show Author Affiliations
Mohammed YousefHussien, Rochester Institute of Technology (United States)
Kelley Garvin, Univ. of Rochester (United States)
Diane Dalecki, Univ. of Rochester (United States)
Eli Saber, Rochester Institute of Technology (United States)
María Helguera, Rochester Institute of Technology (United States)


Published in SPIE Proceedings Vol. 8654:
Visualization and Data Analysis 2013
Pak Chung Wong; David L. Kao; Ming C. Hao; Chaomei Chen, Editor(s)

© SPIE. Terms of Use
Back to Top