activity
20192022
most citedUltrasound Video Summarization using Deep Reinforcement Learning

4 citations · 5 across the 4 of their papers we have counts for

collaborators

6 papers

eess.IV2022

Mesh-based 3D Motion Tracking in Cardiac MRI using Deep Learning

Qingjie Meng, Wenjia Bai, Tianrui Liu +2

3D motion estimation from cine cardiac magnetic resonance (CMR) images is important for the assessment of cardiac function and diagnosis of cardiovascular diseases. Most of the pre…

eess.IV2022

DURRNet: Deep Unfolded Single Image Reflection Removal Network

Jun-Jie Huang, Tianrui Liu, Zhixiong Yang +3

Single image reflection removal problem aims to divide a reflection-contaminated image into a transmission image and a reflection image. It is a canonical blind source separation p…

eess.IV20211 cited

Detecting Hypo-plastic Left Heart Syndrome in Fetal Ultrasound via Disease-specific Atlas Maps

Samuel Budd, Matthew Sinclair, Thomas Day +11

Fetal ultrasound screening during pregnancy plays a vital role in the early detection of fetal malformations which have potential long-term health impacts. The level of skill requi…

cs.CV20204 cited

Ultrasound Video Summarization using Deep Reinforcement Learning

Tianrui Liu, Qingjie Meng, Athanasios Vlontzos +3

Video is an essential imaging modality for diagnostics, e.g. in ultrasound imaging, for endoscopy, or movement assessment. However, video hasn't received a lot of attention in the…

cs.CV2019

Coupled Network for Robust Pedestrian Detection with Gated Multi-Layer Feature Extraction and Deformable Occlusion Handling

Tianrui Liu, Wenhan Luo, Lin Ma +3

Pedestrian detection methods have been significantly improved with the development of deep convolutional neural networks. Nevertheless, detecting small-scaled pedestrians and occlu…

cs.CV2019

Gated Multi-layer Convolutional Feature Extraction Network for Robust Pedestrian Detection

Tianrui Liu, Jun-Jie Huang, Tianhong Dai +2

Pedestrian detection methods have been significantly improved with the development of deep convolutional neural networks. Nevertheless, robustly detecting pedestrians with a large…