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Proceedings Paper

Automated vasculature extraction from placenta images
Author(s): Nizar Almoussa; Brittany Dutra; Bryce Lampe; Pascal Getreuer; Todd Wittman; Carolyn Salafia; Luminita Vese
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Paper Abstract

Recent research in perinatal pathology argues that analyzing properties of the placenta may reveal important information on how certain diseases progress. One important property is the structure of the placental blood vessels, which supply a fetus with all of its oxygen and nutrition. An essential step in the analysis of the vascular network pattern is the extraction of the blood vessels, which has only been done manually through a costly and time-consuming process. There is no existing method to automatically detect placental blood vessels; in addition, the large variation in the shape, color, and texture of the placenta makes it difficult to apply standard edge-detection algorithms. We describe a method to automatically detect and extract blood vessels from a given image by using image processing techniques and neural networks. We evaluate several local features for every pixel, in addition to a novel modification to an existing road detector. Pixels belonging to blood vessel regions have recognizable responses; hence, we use an artificial neural network to identify the pattern of blood vessels. A set of images where blood vessels are manually highlighted is used to train the network. We then apply the neural network to recognize blood vessels in new images. The network is effective in capturing the most prominent vascular structures of the placenta.

Paper Details

Date Published: 12 March 2011
PDF: 10 pages
Proc. SPIE 7962, Medical Imaging 2011: Image Processing, 79621L (12 March 2011); doi: 10.1117/12.878343
Show Author Affiliations
Nizar Almoussa, Univ. of California, Los Angeles (United States)
Brittany Dutra, Univ. of California, Los Angeles (United States)
Bryce Lampe, Harvey Mudd College (United States)
Pascal Getreuer, Univ. of California, Los Angeles (United States)
Todd Wittman, Univ. of California, Los Angeles (United States)
Carolyn Salafia, Placental Analytics, LLC (United States)
Luminita Vese, Univ. of California, Los Angeles (United States)


Published in SPIE Proceedings Vol. 7962:
Medical Imaging 2011: Image Processing
Benoit M. Dawant; David R. Haynor, Editor(s)

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