Original paper
C-ICT for Discovery of Multiple Associations in Multimodal Imaging Data: Application to Fusion of fMRI and DTI Data
Published: Mar 1, 2019
Abstract
Fusing datasets from different brain signal modalities improves accuracy in finding biomarkers of neuropsychiatric diseases. Several approaches, such as joint independent component analysis (ICA) and independent vector analysis (IVA), are useful but fall short of exploring multiple associations between different modalities, especially for the case where one underlying component in one modality might have multiple associations with others in...
Paper Details
Title
C-ICT for Discovery of Multiple Associations in Multimodal Imaging Data: Application to Fusion of fMRI and DTI Data
Published Date
Mar 1, 2019
Citation AnalysisPro
You’ll need to upgrade your plan to Pro
Looking to understand the true influence of a researcher’s work across journals & affiliations?
- Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
- Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.
Notes
History