activity
20182022
most citedAuto-FedAvg: Learnable Federated Averaging for Multi-Institutional Medical Image Segmentation

37 citations · 53 across the 8 of their papers we have counts for

collaborators

11 papers

cs.CV2022

Distance Map Supervised Landmark Localization for MR-TRUS Registration

Xinrui Song, Xuanang Xu, Sheng Xu +4

In this work, we propose to explicitly use the landmarks of prostate to guide the MR-TRUS image registration. We first train a deep neural network to automatically localize a set o…

eess.IV2021

End-to-end Ultrasound Frame to Volume Registration

Hengtao Guo, Xuanang Xu, Sheng Xu +2

Fusing intra-operative 2D transrectal ultrasound (TRUS) image with pre-operative 3D magnetic resonance (MR) volume to guide prostate biopsy can significantly increase the yield. Ho…

cs.CV20216 cited

Cross-modal Attention for MRI and Ultrasound Volume Registration

Xinrui Song, Hengtao Guo, Xuanang Xu +6

Prostate cancer biopsy benefits from accurate fusion of transrectal ultrasound (TRUS) and magnetic resonance (MR) images. In the past few years, convolutional neural networks (CNNs…

eess.IV202137 cited

Auto-FedAvg: Learnable Federated Averaging for Multi-Institutional Medical Image Segmentation

Yingda Xia, Dong Yang, Wenqi Li +15

Federated learning (FL) enables collaborative model training while preserving each participant's privacy, which is particularly beneficial to the medical field. FedAvg is a standar…

cs.CV2020

Transducer Adaptive Ultrasound Volume Reconstruction

Hengtao Guo, Sheng Xu, Bradford J. Wood +1

Reconstructed 3D ultrasound volume provides more context information compared to a sequence of 2D scanning frames, which is desirable for various clinical applications such as ultr…

cs.CV20205 cited

Multi-Domain Image Completion for Random Missing Input Data

Liyue Shen, Wentao Zhu, Xiaosong Wang +9

Multi-domain data are widely leveraged in vision applications taking advantage of complementary information from different modalities, e.g., brain tumor segmentation from multi-par…