Automatic segmentation and therapy follow-up of cerebral glioma in diffusion-tensor images

Giorgio De Nunzio, Marina Donativi, Gabriella Pastore, Lorenzo Bello, Riccardo Soffietti, Andrea Falini, Antonella Castellano

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

Abstract

Gliomas are the most common primary brain tumors, with a typical infiltrative growth pattern along white matter (WM) fibers. Diffusion Tensor Imaging (DTI) is sensitive to the directional diffusion of water along WM tracts, which allows the identification of subtle peritumoral glioma infiltration that are not apparent on conventional Magnetic Resonance imaging. The aim of this study was to characterize pathological and healthy tissue in DTI datasets by statistical texture analysis, developing a Computer Assisted Detection (CAD) technique for cerebral glioma. This system, coupled to voxel-based tumor evolution analysis, could allow objective tumor identification and qualitative and quantitative measurements in the follow-up of patients during chemotherapy. In this paper, preliminary results of tumor segmentation and evolution analysis are shown.

Original languageEnglish
Title of host publicationCIMSA 2010 - IEEE International Conference on Computational Intelligence for Measurement Systems and Applications, Proceedings
Pages43-47
Number of pages5
DOIs
Publication statusPublished - 2010
Event8th IEEE International Conference on Computational Intelligence for Measurement Systems and Applications, CIMSA 2010 - Taranto, Italy
Duration: Sep 6 2010Sep 8 2010

Other

Other8th IEEE International Conference on Computational Intelligence for Measurement Systems and Applications, CIMSA 2010
Country/TerritoryItaly
CityTaranto
Period9/6/109/8/10

Keywords

  • CAD
  • Glioma
  • Neural networks
  • Texture features

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Control and Systems Engineering

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