Diagnosis of brain abnormality using both structural and functional MR images

Yong Fan, Hengyi Rao, Joan Giannetta, Hallam Hurt, Jiongjiong Wang, Christos Davatzikos, Dinggang Shen

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

8 Citations (Scopus)

Abstract

A number of neurological diseases are associated with structural and functional alterations in the brain. This paper presents a method of using both structural and functional MR images for brain disease diagnosis, by machine learning and high-dimensional template warping. First, a high-dimensional template warping technique is used to compute morphological and functional representations for each individual brain in a template space, within a mass preserving framework. Then, statistical regional features are extracted to reduce the dimensionality of morphological and functional representations, as well as to achieve the robustness to registration errors and inter-subject variations. Finally, the most discriminative regional features are selected by a hybrid feature selection method for brain classification, using a nonlinear support vector machine. The proposed method has been applied to classifying the brain images of prenatally cocaine-exposed young adults from those of socioeconomically matched controls, resulting in 91.8% correct classification rate using a leave-one-out cross-validation. Comparison results show the effectiveness of our method and also the importance of simultaneously using both structural and functional images for brain classification.

Original languageEnglish
Title of host publicationAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Pages6585-6588
Number of pages4
DOIs
Publication statusPublished - 2006 Dec 1
Externally publishedYes
Event28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'06 - New York, NY, United States
Duration: 2006 Aug 302006 Sep 3

Other

Other28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'06
CountryUnited States
CityNew York, NY
Period06/8/3006/9/3

Fingerprint

Brain
Cocaine
Support vector machines
Learning systems
Feature extraction

ASJC Scopus subject areas

  • Bioengineering

Cite this

Fan, Y., Rao, H., Giannetta, J., Hurt, H., Wang, J., Davatzikos, C., & Shen, D. (2006). Diagnosis of brain abnormality using both structural and functional MR images. In Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings (pp. 6585-6588). [4030605] https://doi.org/10.1109/IEMBS.2006.260894

Diagnosis of brain abnormality using both structural and functional MR images. / Fan, Yong; Rao, Hengyi; Giannetta, Joan; Hurt, Hallam; Wang, Jiongjiong; Davatzikos, Christos; Shen, Dinggang.

Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings. 2006. p. 6585-6588 4030605.

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

Fan, Y, Rao, H, Giannetta, J, Hurt, H, Wang, J, Davatzikos, C & Shen, D 2006, Diagnosis of brain abnormality using both structural and functional MR images. in Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings., 4030605, pp. 6585-6588, 28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'06, New York, NY, United States, 06/8/30. https://doi.org/10.1109/IEMBS.2006.260894
Fan Y, Rao H, Giannetta J, Hurt H, Wang J, Davatzikos C et al. Diagnosis of brain abnormality using both structural and functional MR images. In Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings. 2006. p. 6585-6588. 4030605 https://doi.org/10.1109/IEMBS.2006.260894
Fan, Yong ; Rao, Hengyi ; Giannetta, Joan ; Hurt, Hallam ; Wang, Jiongjiong ; Davatzikos, Christos ; Shen, Dinggang. / Diagnosis of brain abnormality using both structural and functional MR images. Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings. 2006. pp. 6585-6588
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