128 citations · 178 across the 9 of their papers we have counts for
4 papers · 1 filter
Multimodal Variational Autoencoder: a Barycentric View
Peijie Qiu, Wenhui Zhu, Sayantan Kumar +6
Multiple signal modalities, such as vision and sounds, are naturally present in real-world phenomena. Recently, there has been growing interest in learning generative models, in pa…
HiMAL: A Multimodal Hierarchical Multi-task Auxiliary Learning framework for predicting and explaining Alzheimer disease progression
Sayantan Kumar, Sean Yu, Andrew Michelson +2
Objective: We aimed to develop and validate a novel multimodal framework HiMAL (Hierarchical, Multi-task Auxiliary Learning) framework, for predicting cognitive composite functions…
Analyzing heterogeneity in Alzheimer Disease using multimodal normative modeling on imaging-based ATN biomarkers
Sayantan Kumar, Tom Earnest, Braden Yang +10
INTRODUCTION: Previous studies have applied normative modeling on a single neuroimaging modality to investigate Alzheimer Disease (AD) heterogeneity. We employed a deep learning-ba…
AgileFormer: Spatially Agile Transformer UNet for Medical Image Segmentation
Peijie Qiu, Jin Yang, Sayantan Kumar +2
In the past decades, deep neural networks, particularly convolutional neural networks, have achieved state-of-the-art performance in a variety of medical image segmentation tasks.…