124 citations · 193 across the 13 of their papers we have counts for
13 papers
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…
Auto-FedRL: Federated Hyperparameter Optimization for Multi-institutional Medical Image Segmentation
Pengfei Guo, Dong Yang, Ali Hatamizadeh +14
Federated learning (FL) is a distributed machine learning technique that enables collaborative model training while avoiding explicit data sharing. The inherent privacy-preserving…
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…
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…
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…
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…
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…
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…
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…
Learning Deep Similarity Metric for 3D MR-TRUS Registration
Grant Haskins, Jochen Kruecker, Uwe Kruger +4
Purpose: The fusion of transrectal ultrasound (TRUS) and magnetic resonance (MR) images for guiding targeted prostate biopsy has significantly improved the biopsy yield of aggressi…
Adversarial Image Registration with Application for MR and TRUS Image Fusion
Pingkun Yan, Sheng Xu, Ardeshir R. Rastinehad +1
Robust and accurate alignment of multimodal medical images is a very challenging task, which however is very useful for many clinical applications. For example, magnetic resonance…
A Collaborative Computer Aided Diagnosis (C-CAD) System with Eye-Tracking, Sparse Attentional Model, and Deep Learning
Naji Khosravan, Haydar Celik, Baris Turkbey +3
There are at least two categories of errors in radiology screening that can lead to suboptimal diagnostic decisions and interventions:(i)human fallibility and (ii)complexity of vis…
Gaze2Segment: A Pilot Study for Integrating Eye-Tracking Technology into Medical Image Segmentation
Naji Khosravan, Haydar Celik, Baris Turkbey +9
This study introduced a novel system, called Gaze2Segment, integrating biological and computer vision techniques to support radiologists' reading experience with an automatic image…