14 citations · 44 across the 11 of their papers we have counts for
11 papers
Privileged Anatomical and Protocol Discrimination in Trackerless 3D Ultrasound Reconstruction
Qi Li, Ziyi Shen, Qian Li +5
Three-dimensional (3D) freehand ultrasound (US) reconstruction without using any additional external tracking device has seen recent advances with deep neural networks (DNNs). In t…
Combiner and HyperCombiner Networks: Rules to Combine Multimodality MR Images for Prostate Cancer Localisation
Wen Yan, Bernard Chiu, Ziyi Shen +8
One of the distinct characteristics in radiologists' reading of multiparametric prostate MR scans, using reporting systems such as PI-RADS v2.1, is to score individual types of MR…
Active learning using adaptable task-based prioritisation
Shaheer U. Saeed, João Ramalhinho, Mark Pinnock +9
Supervised machine learning-based medical image computing applications necessitate expert label curation, while unlabelled image data might be relatively abundant. Active learning…
Trackerless freehand ultrasound with sequence modelling and auxiliary transformation over past and future frames
Qi Li, Ziyi Shen, Qian Li +5
Three-dimensional (3D) freehand ultrasound (US) reconstruction without a tracker can be advantageous over its two-dimensional or tracked counterparts in many clinical applications.…
Collaborative Quantization Embeddings for Intra-Subject Prostate MR Image Registration
Ziyi Shen, Qianye Yang, Yuming Shen +9
Image registration is useful for quantifying morphological changes in longitudinal MR images from prostate cancer patients. This paper describes a development in improving the lear…
You Never Cluster Alone
Yuming Shen, Ziyi Shen, Menghan Wang +3
Recent advances in self-supervised learning with instance-level contrastive objectives facilitate unsupervised clustering. However, a standalone datum is not perceiving the context…
Modeling and Enhancing Low-quality Retinal Fundus Images
Ziyi Shen, Huazhu Fu, Jianbing Shen +1
Retinal fundus images are widely used for the clinical screening and diagnosis of eye diseases. However, fundus images captured by operators with various levels of experience have…
Human-Aware Motion Deblurring
Ziyi Shen, Wenguan Wang, Xiankai Lu +4
This paper proposes a human-aware deblurring model that disentangles the motion blur between foreground (FG) humans and background (BG). The proposed model is based on a triple-bra…
Exploiting Semantics for Face Image Deblurring
Ziyi Shen, Wei-Sheng Lai, Tingfa Xu +2
In this paper, we propose an effective and efficient face deblurring algorithm by exploiting semantic cues via deep convolutional neural networks. As the human faces are highly str…
Stochastic Channel Decorrelation Network and Its Application to Visual Tracking
Jie Guo, Tingfa Xu, Shenwang Jiang +1
Deep convolutional neural networks (CNNs) have dominated many computer vision domains because of their great power to extract good features automatically. However, many deep CNNs-b…
Deep Semantic Face Deblurring
Ziyi Shen, Wei-Sheng Lai, Tingfa Xu +2
In this paper, we present an effective and efficient face deblurring algorithm by exploiting semantic cues via deep convolutional neural networks (CNNs). As face images are highly…