Predicting the growth probability function of tumors in medical images.

Kwangsik Nho, Donald E. Brown

Research output: Contribution to journalArticle

Abstract

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 languageEnglish (US)
Pages (from-to)1068
Number of pages1
JournalAMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium
StatePublished - 2008
Externally publishedYes

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Growth
Neoplasms
Data Mining
Direction compound

ASJC Scopus subject areas

  • Medicine(all)

Cite this

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