3 papers
eess.IV2025
A Generative Imputation Method for Multimodal Alzheimer's Disease Diagnosis
Reihaneh Hassanzadeh, Anees Abrol, Hamid Reza Hassanzadeh +1
Multimodal data analysis can lead to more accurate diagnoses of brain disorders due to the complementary information that each modality adds. However, a major challenge of using mu…
eess.IV2025
MultiViT2: A Data-augmented Multimodal Neuroimaging Prediction Framework via Latent Diffusion Model
Bi Yuda, Jia Sihan, Gao Yutong +3
Multimodal medical imaging integrates diverse data types, such as structural and functional neuroimaging, to provide complementary insights that enhance deep learning predictions a…
cs.LG2019
Prediction of Progression to Alzheimer's disease with Deep InfoMax
Alex Fedorov, R Devon Hjelm, Anees Abrol +4
Arguably, unsupervised learning plays a crucial role in the majority of algorithms for processing brain imaging. A recently introduced unsupervised approach Deep InfoMax (DIM) is a…