activity
20192023
most citedFedlearn-Algo: A flexible open-source privacy-preserving machine learning platform

12 citations · 23 across the 7 of their papers we have counts for

collaborators

7 papers

eess.IV2023

DMCVR: Morphology-Guided Diffusion Model for 3D Cardiac Volume Reconstruction

Xiaoxiao He, Chaowei Tan, Ligong Han +4

Accurate 3D cardiac reconstruction from cine magnetic resonance imaging (cMRI) is crucial for improved cardiovascular disease diagnosis and understanding of the heart's motion. How…

eess.IV2023

Dealing With Heterogeneous 3D MR Knee Images: A Federated Few-Shot Learning Method With Dual Knowledge Distillation

Xiaoxiao He, Chaowei Tan, Bo Liu +8

Federated Learning has gained popularity among medical institutions since it enables collaborative training between clients (e.g., hospitals) without aggregating data. However, due…

eess.IV2022

Recursive 3D Segmentation of Shoulder Joint with Coarse-scanned MR Image

Xiaoxiao He, Chaowei Tan, Virak Tan +1

For diagnosis of shoulder illness, it is essential to look at the morphology deviation of scapula and humerus from the medical images that are acquired from Magnetic Resonance (MR)…

cs.LG2021★ 12 cited

Fedlearn-Algo: A flexible open-source privacy-preserving machine learning platform

Bo Liu, Chaowei Tan, Jiazhou Wang +7

In this paper, we present Fedlearn-Algo, an open-source privacy preserving machine learning platform. We use this platform to demonstrate our research and development results on pr…

cs.CV2021★ 8 cited

Data Augmentation for Object Detection via Differentiable Neural Rendering

Guanghan Ning, Guang Chen, Chaowei Tan +3

It is challenging to train a robust object detector under the supervised learning setting when the annotated data are scarce. Thus, previous approaches tackling this problem are in…

eess.IV2019★ 2 cited

Collaborative Multi-agent Learning for MR Knee Articular Cartilage Segmentation

Chaowei Tan, Zhennan Yan, Shaoting Zhang +2

The 3D morphology and quantitative assessment of knee articular cartilages (i.e., femoral, tibial, and patellar cartilage) in magnetic resonance (MR) imaging is of great importance…