A machine learning pipeline for three-way classification of Alzheimer patients from structural magnetic resonance images of the brain

Sriraam Natarajan, Saket Joshi, Baidya N. Saha, Adam Edwards, Tushar Khot, Elizabeth Moody, Kristian Kersting, Christopher T. Whitlow, Joseph A Maldjian

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

4 Scopus citations

Abstract

Magnetic resonance imaging (MRI) has emerged as an important tool to identify intermediate biomarkers of Alzheimer's disease (AD) due to its ability to measure regional changes in the brain that are thought to reflect disease severity and progression. In this paper, we set out a novel pipeline that uses volumetric MRI data collected from different subjects as input and classifies them into one of three classes: AD, mild cognitive impairment (MCI) and cognitively normal (CN). Our pipeline consists of three stages-(1) a segmentation layer where brain MRI data is divided into clinically relevant regions, (2) a classification layer that uses relational learning algorithms to make pair wise predictions between the three classes, and (3)a combination layer that combines the results of the different classes to obtain the final classification. One of the key features of our proposed approach is that it allows for domain expert's knowledge to guide the learning in all the layers. We evaluate our pipeline on 397 patients acquired from the Alzheimer's Disease Neuroimaging Initiative and demonstrate that it obtains state-of the-art performance with minimal feature engineering.

Original languageEnglish (US)
Title of host publicationProceedings - 2012 11th International Conference on Machine Learning and Applications, ICMLA 2012
Pages203-208
Number of pages6
Volume1
DOIs
Publication statusPublished - Dec 1 2012
Event11th IEEE International Conference on Machine Learning and Applications, ICMLA 2012 - Boca Raton, FL, United States
Duration: Dec 12 2012Dec 15 2012

Other

Other11th IEEE International Conference on Machine Learning and Applications, ICMLA 2012
CountryUnited States
CityBoca Raton, FL
Period12/12/1212/15/12

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Keywords

  • Classification
  • fMRI
  • Machine Learning
  • Medical Imaging
  • Probabilistic Reasoning

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Education

Cite this

Natarajan, S., Joshi, S., Saha, B. N., Edwards, A., Khot, T., Moody, E., ... Maldjian, J. A. (2012). A machine learning pipeline for three-way classification of Alzheimer patients from structural magnetic resonance images of the brain. In Proceedings - 2012 11th International Conference on Machine Learning and Applications, ICMLA 2012 (Vol. 1, pp. 203-208). [6406613] https://doi.org/10.1109/ICMLA.2012.42