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Assessment of Vascular Network Segmentation
Jack Collins, Christopher Kurcz, Curtis Lisle, Yanling Liu, Enrique Zudaire
Pages - 584 - 599     |    Revised - 31-01-2011     |    Published - 08-02-2011
Volume - 4   Issue - 6    |    Publication Date - January / February  Table of Contents
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KEYWORDS
vessel segmentation , network comparison, quantitative analysis, segmentation quality, segmentation accuracy
ABSTRACT
We present an analysis framework to assess the quality and accuracy of vessel segmentation algorithms for three dimensional images. We generate synthetic (in silico) vessel models which act as ground truth and are constructed to embody varying morphological features. These models are transformed into images constructed under different levels of contrast, noise, and intensity. To demonstrate the use of our framework, we implemented two segmentation algorithms and compare the results to the ground truth model using several measures to quantify the accuracy and quality of segmentation. Furthermore, we collect metrics which describe the characteristics of the vessels it fails to segment. Our approach is illustrated with several examples. Funded by NCI Contract No. HHSN261200800001E.
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Dr. Jack Collins
- United States of America
Dr. Christopher Kurcz
SAIC-Frederick - United States of America
chris.kurcz@gmail.com
Dr. Curtis Lisle
- United States of America
Dr. Yanling Liu
- United States of America
Dr. Enrique Zudaire
- United States of America