A system framework for the integration and analysis of multi-modal spatiotemporal data streams: a case study in MS lesion analysis

Fillia Makedon, Yuhang Wang, Tilmann Steinberg, Heather Wishart, Andrew Saykin, James Ford, Song Ye, Li Shen

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

3 Scopus citations

Abstract

This paper describes the development of MS-Analyze, a system framework to analyze and detect patterns in brain pathology of multiple sclerosis (MS) as the disease progresses over time. We are building the system to collect, analyze and integrate disparate data extracted from observing the behavior of MS lesions and surrounding pathology on magnetic resonance imaging (MRI) over time. Multiple sclerosis (MS) is a brain disease that affects over 250,000 people in the USA alone. Various MRI sequences are used to monitor brain changes during the natural progression of the disease, and as different drug treatments are explored to slow the disease. The outcome is a set of disparate data streams that need to be correlated efficiently to discover patterns of MS pathology and plan treatment. However, MS data analysis faces the same computational problems as many other scientific domains with heterogeneous data streams: the need for integration of and access to large amounts of data, beyond what is normally available to any one given laboratory. MS-Analyze addresses both of these challenges by combining data collection, data fusion, data analysis, and secure data sharing. MS is a good application to demonstrate the system because it offers rich data that challenge the system development.

Original languageEnglish (US)
Title of host publicationConference Proceedings - 1st International IEEE EMBS Conference on Neural Engineering
EditorsLaura J. Wolf, Jodi L. Strock
PublisherIEEE Computer Society
Pages495-498
Number of pages4
ISBN (Electronic)0780375793
DOIs
StatePublished - Jan 1 2003
Event1st International IEEE EMBS Conference on Neural Engineering - Capri Island, Italy
Duration: Mar 20 2003Mar 22 2003

Publication series

NameInternational IEEE/EMBS Conference on Neural Engineering, NER
Volume2003-January
ISSN (Print)1948-3546
ISSN (Electronic)1948-3554

Other

Other1st International IEEE EMBS Conference on Neural Engineering
CountryItaly
CityCapri Island
Period3/20/033/22/03

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Keywords

  • Data analysis
  • Diseases
  • Image analysis
  • Lesions
  • Magnetic analysis
  • Magnetic resonance imaging
  • Multiple sclerosis
  • Pathology
  • Pattern analysis
  • Spatiotemporal phenomena

ASJC Scopus subject areas

  • Artificial Intelligence
  • Mechanical Engineering

Cite this

Makedon, F., Wang, Y., Steinberg, T., Wishart, H., Saykin, A., Ford, J., Ye, S., & Shen, L. (2003). A system framework for the integration and analysis of multi-modal spatiotemporal data streams: a case study in MS lesion analysis. In L. J. Wolf, & J. L. Strock (Eds.), Conference Proceedings - 1st International IEEE EMBS Conference on Neural Engineering (pp. 495-498). [1196871] (International IEEE/EMBS Conference on Neural Engineering, NER; Vol. 2003-January). IEEE Computer Society. https://doi.org/10.1109/CNE.2003.1196871