Quantifying evolving processes in multimodal 3D medical images

Yuhang Wang, Tilmann Steinberg, Fillia Makedon, James Ford, Heather Wishart, Andrew Saykin

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

Abstract

Quantitative measurements of changes in evolving brain pathology, such as multiple sclerosis lesions and brain tumors, are important for clinicians to perform pertinent diagnoses and to help in patient follow-up. Lesions or tumors can vary over time in size, shape, location and composition because of natural pathological processes or the effect of a drug treatment or therapy. In the past, people have used as a quantitative measurement the change in total or regional lesion/tumor volume. In this paper we propose a new model to quantify changes in evolving processes in multimodal 3D medical images. We believe this model reflects changes in pathology more accurately because it simultaneously takes into account information in multiple imaging modalities and the location of lesion/tumor voxels. We demonstrate the effectiveness of this model with experiments on synthetic lesion data.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag
Pages92-100
Number of pages9
Volume2879
ISBN (Print)3540204644
DOIs
StatePublished - 2003
Externally publishedYes
Event6th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2003 - Montreal, Canada
Duration: Nov 15 2003Nov 18 2003

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2879
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other6th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2003
CountryCanada
CityMontreal
Period11/15/0311/18/03

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

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  • Cite this

    Wang, Y., Steinberg, T., Makedon, F., Ford, J., Wishart, H., & Saykin, A. (2003). Quantifying evolving processes in multimodal 3D medical images. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2879, pp. 92-100). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2879). Springer Verlag. https://doi.org/10.1007/978-3-540-39903-2_13