11 citations · 26 across the 18 of their papers we have counts for
5 papers · 1 filter
Longitudinal Correlation Analysis for Decoding Multi-Modal Brain Development
Qingyu Zhao, Ehsan Adeli, Kilian M. Pohl
Starting from childhood, the human brain restructures and rewires throughout life. Characterizing such complex brain development requires effective analysis of longitudinal and mul…
Metadata Normalization
Mandy Lu, Qingyu Zhao, Jiequan Zhang +4
Batch Normalization (BN) and its variants have delivered tremendous success in combating the covariate shift induced by the training step of deep learning methods. While these tech…
Self-Supervised Longitudinal Neighbourhood Embedding
Jiahong Ouyang, Qingyu Zhao, Ehsan Adeli +4
Longitudinal MRIs are often used to capture the gradual deterioration of brain structure and function caused by aging or neurological diseases. Analyzing this data via machine lear…
Representation Disentanglement for Multi-modal brain MR Analysis
Jiahong Ouyang, Ehsan Adeli, Kilian M. Pohl +2
Multi-modal MRIs are widely used in neuroimaging applications since different MR sequences provide complementary information about brain structures. Recent works have suggested tha…
Going Beyond Saliency Maps: Training Deep Models to Interpret Deep Models
Zixuan Liu, Ehsan Adeli, Kilian M. Pohl +1
Interpretability is a critical factor in applying complex deep learning models to advance the understanding of brain disorders in neuroimaging studies. To interpret the decision pr…