Joint estimation of multiple clinical variables of neurological diseases from imaging patterns

Yong Fan, Daniel Kaufer, Dinggang Shen

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

16 Citations (Scopus)

Abstract

This paper presents a method to estimate multiple clinical variables associated with neurological pathologies from brain images, aiming to quantitatively evaluate continuous transition of neurological pathologies from the normal to diseased state. Built upon morphological measures derived from structural MR brain images, a Bayesian regression method is developed to jointly model multiple clinical variables for capturing their inherent correlations and suppressing noise. Coupled with a feature selection technique, the regression method is used to build a joint estimator of multiple clinical variables associated with Alzheimer's disease from structural MR brain images of elderly individuals. The cross-validation results demonstrate that the proposed method has superior performance over existing techniques.

Original languageEnglish
Title of host publication2010 7th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2010 - Proceedings
Pages852-855
Number of pages4
DOIs
Publication statusPublished - 2010 Aug 9
Externally publishedYes
Event7th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2010 - Rotterdam, Netherlands
Duration: 2010 Apr 142010 Apr 17

Other

Other7th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2010
CountryNetherlands
CityRotterdam
Period10/4/1410/4/17

Fingerprint

Brain
Joints
Pathology
Imaging techniques
Bayes Theorem
Noise
Feature extraction
Alzheimer Disease

Keywords

  • ADAS-Cog
  • Alzheimer's disease
  • Bayesian regression
  • MMSE
  • Structural MR brain image

ASJC Scopus subject areas

  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging

Cite this

Fan, Y., Kaufer, D., & Shen, D. (2010). Joint estimation of multiple clinical variables of neurological diseases from imaging patterns. In 2010 7th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2010 - Proceedings (pp. 852-855). [5490120] https://doi.org/10.1109/ISBI.2010.5490120

Joint estimation of multiple clinical variables of neurological diseases from imaging patterns. / Fan, Yong; Kaufer, Daniel; Shen, Dinggang.

2010 7th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2010 - Proceedings. 2010. p. 852-855 5490120.

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

Fan, Y, Kaufer, D & Shen, D 2010, Joint estimation of multiple clinical variables of neurological diseases from imaging patterns. in 2010 7th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2010 - Proceedings., 5490120, pp. 852-855, 7th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2010, Rotterdam, Netherlands, 10/4/14. https://doi.org/10.1109/ISBI.2010.5490120
Fan Y, Kaufer D, Shen D. Joint estimation of multiple clinical variables of neurological diseases from imaging patterns. In 2010 7th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2010 - Proceedings. 2010. p. 852-855. 5490120 https://doi.org/10.1109/ISBI.2010.5490120
Fan, Yong ; Kaufer, Daniel ; Shen, Dinggang. / Joint estimation of multiple clinical variables of neurological diseases from imaging patterns. 2010 7th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2010 - Proceedings. 2010. pp. 852-855
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