1.1k citations · 1.5k across the 36 of their papers we have counts for
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SimCVD: Simple Contrastive Voxel-Wise Representation Distillation for Semi-Supervised Medical Image Segmentation
Chenyu You, Yuan Zhou, Ruihan Zhao +2
Automated segmentation in medical image analysis is a challenging task that requires a large amount of manually labeled data. However, most existing learning-based approaches usual…
Synthesizing Multi-Tracer PET Images for Alzheimer's Disease Patients using a 3D Unified Anatomy-aware Cyclic Adversarial Network
Bo Zhou, Rui Wang, Ming-Kai Chen +6
Positron Emission Tomography (PET) is an important tool for studying Alzheimer's disease (AD). PET scans can be used as diagnostics tools, and to provide molecular characterization…
Anatomy-Constrained Contrastive Learning for Synthetic Segmentation without Ground-truth
Bo Zhou, Chi Liu, James S. Duncan
A large amount of manual segmentation is typically required to train a robust segmentation network so that it can segment objects of interest in a new imaging modality. The manual…
Estimating Reproducible Functional Networks Associated with Task Dynamics using Unsupervised LSTMs
Nicha C. Dvornek, Pamela Ventola, James S. Duncan
We propose a method for estimating more reproducible functional networks that are more strongly associated with dynamic task activity by using recurrent neural networks with long s…
Momentum Contrastive Voxel-wise Representation Learning for Semi-supervised Volumetric Medical Image Segmentation
Chenyu You, Ruihan Zhao, Lawrence Staib +1
Contrastive learning (CL) aims to learn useful representation without relying on expert annotations in the context of medical image segmentation. Existing approaches mainly contras…
Demographic-Guided Attention in Recurrent Neural Networks for Modeling Neuropathophysiological Heterogeneity
Nicha C. Dvornek, Xiaoxiao Li, Juntang Zhuang +2
Heterogeneous presentation of a neurological disorder suggests potential differences in the underlying pathophysiological changes that occur in the brain. We propose to model heter…
MALI: A memory efficient and reverse accurate integrator for Neural ODEs
Juntang Zhuang, Nicha C. Dvornek, Sekhar Tatikonda +1
Neural ordinary differential equations (Neural ODEs) are a new family of deep-learning models with continuous depth. However, the numerical estimation of the gradient in the contin…
Multiple-shooting adjoint method for whole-brain dynamic causal modeling
Juntang Zhuang, Nicha Dvornek, Sekhar Tatikonda +3
Dynamic causal modeling (DCM) is a Bayesian framework to infer directed connections between compartments, and has been used to describe the interactions between underlying neural p…