Ordinal ranking for detecting mild cognitive impairment and Alzheimer's disease based on multimodal neuroimages and CSF biomarkers

摘要: Early diagnosis of Alzheimer's disease (AD) based on neuroimaging and fluid biomarker data has attracted a lot interest in medical image analysis. Most existing studies have been focusing two-class classification problems, e.g., distinguishing AD patients from cognitive normal (CN) elderly or mild impairment (MCI) individuals CN elderly. However, to achieve the goal early AD, we need identify with MCI, especially MCI who will convert single setting, which essentially is multi-class problem. In this paper, propose an ordinal ranking method for CN, non-converter (MCI-NC), converter (MCI-C), at individual level, taking into account inherent severity brain damage caused by aging, rather than formulating as Experiment results indicate that proposed can better performance traditional techniques multimodal CSF ADNI.