activity
20182022
most citedCross-modal Attention for MRI and Ultrasound Volume Registration

6 citations · 11 across the 6 of their papers we have counts for

collaborators

8 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…

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.CV20201 cited

Sensorless Freehand 3D Ultrasound Reconstruction via Deep Contextual Learning

Hengtao Guo, Sheng Xu, Bradford Wood +1

Transrectal ultrasound (US) is the most commonly used imaging modality to guide prostate biopsy and its 3D volume provides even richer context information. Current methods for 3D v…

eess.IV20194 cited

Unified Multi-scale Feature Abstraction for Medical Image Segmentation

Xi Fang, Bo Du, Sheng Xu +2

Automatic medical image segmentation, an essential component of medical image analysis, plays an importantrole in computer-aided diagnosis. For example, locating and segmenting the…