The dynamics of a tumor can be studied using a feature-based stochastic method to predict the temporal and spatial growth of the tumor. A posterior probability of growth function is incorporated into the interacting particle model definition, and the probability influences growth direction at each location. Using features derived from images and data-mining, the growth probability function is predicted and tested to investigate the ability of the derived feature values to explain the tumor evolution.
|Original language||English (US)|
|Number of pages||1|
|Journal||AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium|
|State||Published - 2008|
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