Discriminative MR Image Feature Analysis for Automatic Schizophrenia and Alzheimer's Disease Classification

Yanxi Liu, Leonid Teverovskiy, Owen Carmichael, R. Kikinis, M. Shenton, C.S. Carter, V.A. Stenger, S. Davis, Howard Aizenstein, Jim Becker, Oscar Lopez, and Carolyn Meltzer
Proceedings of the 7th International Conference on MedicalImage Computing and Computer Aided Intervention (MICCAI '04), October, 2004, pp. 393 - 401.


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Abstract
We construct a computational framework for automatic central nervous system (CNS) disease discrimination using high resolution Magnetic Resonance Images (MRI) of human brains. More than 3000 MR image features are extracted, forming a high dimensional coarse-to-fine hierarchical image description that quantifies brain asymmetry, texture and statistical properties in corresponding local regions of the brain. Discriminative image feature subspaces are computed, evaluated and selected automatically. Our initial experimental results show 100% and 90% separability between chronicle schizophrenia (SZ) and first episode SZ versus their respective matched controls. Under the same computational framework, we also find higher than 95% separability among Alzheimer's Disease, mild cognitive impairment patients, and their matched controls. An average of 88% classification success rate is achieved using leave-one-out cross validation on five different well-chosen patient-control image sets of sizes from 15 to 27 subjects per disease class.

Notes
Associated Center(s) / Consortia: Vision and Autonomous Systems Center and Medical Robotics Technology Center
Associated Lab(s) / Group(s): Biomedical Image Analysis
Associated Project(s): Predicting Risk of Alzheimer\'s Disease From Shape Features
Number of pages: 9

Text Reference
Yanxi Liu, Leonid Teverovskiy, Owen Carmichael, R. Kikinis, M. Shenton, C.S. Carter, V.A. Stenger, S. Davis, Howard Aizenstein, Jim Becker, Oscar Lopez, and Carolyn Meltzer, "Discriminative MR Image Feature Analysis for Automatic Schizophrenia and Alzheimer's Disease Classification," Proceedings of the 7th International Conference on MedicalImage Computing and Computer Aided Intervention (MICCAI '04), October, 2004, pp. 393 - 401.

BibTeX Reference
@inproceedings{Liu_2004_4678,
   author = "Yanxi Liu and Leonid Teverovskiy and Owen Carmichael and R. Kikinis and M. Shenton and C.S. Carter and V.A. Stenger and S. Davis and Howard Aizenstein and Jim Becker and Oscar Lopez and Carolyn Meltzer",
   title = "Discriminative MR Image Feature Analysis for Automatic Schizophrenia and Alzheimer's Disease Classification",
   booktitle = "Proceedings of the 7th International Conference on MedicalImage Computing and Computer Aided Intervention (MICCAI '04)",
   pages = "393 - 401",
   month = "October",
   year = "2004",
}