@inproceedings{d0ae442097f9435e8a45fc23daa5d12e,
title = "Tumor angiogenesis assessment using multi-fluorescent scans on murine slices by Markov random field framework",
abstract = "The fundamental role of vascular supply in tumor growth makes the evaluation of the angiogenesis crucial in assessing effect of anti-angiogenic therapies. Since many years, such therapies are designed to inhibit the vascular endothelial growth factor (VEGF). To contribute to the assessment of anti-angiogenic agent (Pazopanib) effect on vascular and cellular structures, we acquired data from tumors extracted from a murine tumor model using Multi- Fluorescence Scanning. In this paper, we implemented an unsupervised algorithm combining the Watershed segmentation and Markov Random Field model (MRF). This algorithm allowed us to quantify the proportion of apoptotic endothelial cells and to generate maps according to cell density. Stronger association between apoptosis and endothelial cells was revealed in the tumors receiving anti-angiogenic therapy (n = 4) as compared to those receiving placebo (n = 4). A high percentage of apoptotic cells in the tumor area are endothelial. Lower density cells were detected in tumor slices presenting higher apoptotic endothelial areas.",
keywords = "Anti-angiogenic, GMM, MRF, Pazopanib, VEGF, apoptosis, multi-fluorescence images, watershed",
author = "Oumeima Laifa and {Le Guillou-Buffello}, Delphine and Daniel Racoceanu",
note = "Publisher Copyright: {\textcopyright} 2017 SPIE.; 13th International Conference on Medical Information Processing and Analysis, SIPAIM 2017 ; Conference date: 05-10-2017 Through 07-10-2017",
year = "2017",
doi = "10.1117/12.2285924",
language = "English",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Natasha Lepore and Jorge Brieva and Garcia, {Juan David} and Eduardo Romero",
booktitle = "13th International Conference on Medical Information Processing and Analysis",
}