activity
20162023
most citedMPRAD: A Multiparametric Radiomics Framework

53 citations · 136 across the 12 of their papers we have counts for

collaborators

14 papers

cs.LG2023★ 4 cited

A framework for dynamically training and adapting deep reinforcement learning models to different, low-compute, and continuously changing radiology deployment environments

Guangyao Zheng, Shuhao Lai, Vladimir Braverman +2

While Deep Reinforcement Learning has been widely researched in medical imaging, the training and deployment of these models usually require powerful GPUs. Since imaging environmen…

cs.LG2023

Multi-environment lifelong deep reinforcement learning for medical imaging

Guangyao Zheng, Shuhao Lai, Vladimir Braverman +2

Deep reinforcement learning(DRL) is increasingly being explored in medical imaging. However, the environments for medical imaging tasks are constantly evolving in terms of imaging…

cs.LG2023★ 3 cited

Asynchronous Decentralized Federated Lifelong Learning for Landmark Localization in Medical Imaging

Guangyao Zheng, Michael A. Jacobs, Vladimir Braverman +1

Federated learning is a recent development in the machine learning area that allows a system of devices to train on one or more tasks without sharing their data to a single locatio…

cs.LG2023★ 2 cited

Selective experience replay compression using coresets for lifelong deep reinforcement learning in medical imaging

Guangyao Zheng, Samson Zhou, Vladimir Braverman +2

Selective experience replay is a popular strategy for integrating lifelong learning with deep reinforcement learning. Selective experience replay aims to recount selected experienc…

eess.IV2021★ 22 cited

Cross-Domain Federated Learning in Medical Imaging

Vishwa S Parekh, Shuhao Lai, Vladimir Braverman +4

Federated learning is increasingly being explored in the field of medical imaging to train deep learning models on large scale datasets distributed across different data centers wh…

eess.IV2019★ 2 cited

Multiparametric Deep Learning Tissue Signatures for Muscular Dystrophy: Preliminary Results

Alex E. Bocchieri, Vishwa S. Parekh, Kathryn R. Wagner. Shivani Ahlawat +3

A current clinical challenge is identifying limb girdle muscular dystrophy 2I(LGMD2I)tissue changes in the thighs, in particular, separating fat, fat-infiltrated muscle, and muscle…