Assessing clinical progression from subjective cognitive decline to mild cognitive impairment with incomplete multi-modal neuroimages.

ABSTRACT: Accurately assessing clinical progression from subjective cognitive decline (SCD) to mild cognitive impairment (MCI) is crucial for early intervention of pathological cognitive decline. Multi-modal neuroimaging data such as T1-weighted magnetic resonance imaging (MRI) and positron emission tomography (PET), help provide objective and supplementary disease biomarkers for computer-aided diagnosis of MCI. However, there are few studies dedicated to SCD progression prediction since subjects usually lack one or more imaging modalities. Besides, one usually has a limited number (e.g., tens) of SCD subjects, negatively affecting model robustness. To this end, we propose a Joint neuroimage Synthesis and Representation Learning (JSRL) framework for SCD conversion prediction using incomplete multi-m

SUBMITTER: Liu Y 

PROVIDER: S-EPMC8678365 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature