Modeling Tumor Growth: From Differential Deformable Models to Growth Prediction of Tumors Detected in PET Images

M. Garbey, G. Zouridakis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Scopus citations

Abstract

Modeling of a growing tumor over time is extremely difficult, because of the complex biological phenomena underlying cancer proliferation. Existing models can mostly describe in vitro experiments of spherically-shaped avascular tumors, but they cannot match the highly heterogeneous and complex-shaped tumors seen in cancer patients. We propose a new time-dependent geometric deformable model that can characterize tumors of complex shape, such as vascular tumors. Preliminary result show that such a model can provide an adequate framework for analyzing and predicting the growth of tumors seen in PET images of cancer patients.

Original languageEnglish (US)
Title of host publicationAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
EditorsR.S. Leder
Pages2687-2690
Number of pages4
Volume3
StatePublished - 2003
EventA New Beginning for Human Health: Proceedings of the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society - Cancun, Mexico
Duration: Sep 17 2003Sep 21 2003

Other

OtherA New Beginning for Human Health: Proceedings of the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
CountryMexico
CityCancun
Period9/17/039/21/03

Keywords

  • Cancer
  • PET image analysis
  • Tumor modeling

ASJC Scopus subject areas

  • Bioengineering

Fingerprint Dive into the research topics of 'Modeling Tumor Growth: From Differential Deformable Models to Growth Prediction of Tumors Detected in PET Images'. Together they form a unique fingerprint.

Cite this