175 citations · 212 across the 33 of their papers we have counts for
19 papers · 1 filter
MTCNet: Motion and Topology Consistency Guided Learning for Mitral Valve Segmentationin 4D Ultrasound
Rusi Chen, Yuanting Yang, Jiezhi Yao +12
Mitral regurgitation is one of the most prevalent cardiac disorders. Four-dimensional (4D) ultrasound has emerged as the primary imaging modality for assessing dynamic valvular mor…
UltraTwin: Towards Cardiac Anatomical Twin Generation from Multi-view 2D Ultrasound
Junxuan Yu, Yaofei Duan, Yuhao Huang +22
Echocardiography is routine for cardiac examination. However, 2D ultrasound (US) struggles with accurate metric calculation and direct observation of 3D cardiac structures. Moreove…
Non-Adversarial Learning: Vector-Quantized Common Latent Space for Multi-Sequence MRI
Luyi Han, Tao Tan, Tianyu Zhang +7
Adversarial learning helps generative models translate MRI from source to target sequence when lacking paired samples. However, implementing MRI synthesis with adversarial learning…
Learned Local Attention Maps for Synthesising Vessel Segmentations
Yash Deo, Rodrigo Bonazzola, Haoran Dou +5
Magnetic resonance angiography (MRA) is an imaging modality for visualising blood vessels. It is useful for several diagnostic applications and for assessing the risk of adverse ev…
Shape-guided Conditional Latent Diffusion Models for Synthesising Brain Vasculature
Yash Deo, Haoran Dou, Nishant Ravikumar +2
The Circle of Willis (CoW) is the part of cerebral vasculature responsible for delivering blood to the brain. Understanding the diverse anatomical variations and configurations of…
A Conditional Flow Variational Autoencoder for Controllable Synthesis of Virtual Populations of Anatomy
Haoran Dou, Nishant Ravikumar, Alejandro F. Frangi
The generation of virtual populations (VPs) of anatomy is essential for conducting in silico trials of medical devices. Typically, the generated VP should capture sufficient variab…
GSMorph: Gradient Surgery for cine-MRI Cardiac Deformable Registration
Haoran Dou, Ning Bi, Luyi Han +7
Deep learning-based deformable registration methods have been widely investigated in diverse medical applications. Learning-based deformable registration relies on weighted objecti…
An Explainable Deep Framework: Towards Task-Specific Fusion for Multi-to-One MRI Synthesis
Luyi Han, Tianyu Zhang, Yunzhi Huang +6
Multi-sequence MRI is valuable in clinical settings for reliable diagnosis and treatment prognosis, but some sequences may be unusable or missing for various reasons. To address th…
A Generative Shape Compositional Framework to Synthesise Populations of Virtual Chimaeras
Haoran Dou, Seppo Virtanen, Nishant Ravikumar +1
Generating virtual populations of anatomy that capture sufficient variability while remaining plausible is essential for conducting in-silico trials of medical devices. However, no…
Localizing the Recurrent Laryngeal Nerve via Ultrasound with a Bayesian Shape Framework
Haoran Dou, Luyi Han, Yushuang He +6
Tumor infiltration of the recurrent laryngeal nerve (RLN) is a contraindication for robotic thyroidectomy and can be difficult to detect via standard laryngoscopy. Ultrasound (US)…
Deformable Registration of Brain MR Images via a Hybrid Loss
Luyi Han, Haoran Dou, Yunzhi Huang +1
Unsupervised learning strategy is widely adopted by the deformable registration models due to the lack of ground truth of deformation fields. These models typically depend on the i…
Agent with Warm Start and Adaptive Dynamic Termination for Plane Localization in 3D Ultrasound
Xin Yang, Haoran Dou, Ruobing Huang +9
Accurate standard plane (SP) localization is the fundamental step for prenatal ultrasound (US) diagnosis. Typically, dozens of US SPs are collected to determine the clinical diagno…
Contrastive Rendering for Ultrasound Image Segmentation
Haoming Li, Xin Yang, Jiamin Liang +12
Ultrasound (US) image segmentation embraced its significant improvement in deep learning era. However, the lack of sharp boundaries in US images still remains an inherent challenge…
Hybrid Attention for Automatic Segmentation of Whole Fetal Head in Prenatal Ultrasound Volumes
Xin Yang, Xu Wang, Yi Wang +6
Background and Objective: Biometric measurements of fetal head are important indicators for maternal and fetal health monitoring during pregnancy. 3D ultrasound (US) has unique adv…
Synthesis and Edition of Ultrasound Images via Sketch Guided Progressive Growing GANs
Jiamin Liang, Xin Yang, Haoming Li +10
Ultrasound (US) is widely accepted in clinic for anatomical structure inspection. However, lacking in resources to practice US scan, novices often struggle to learn the operation s…
Remove Appearance Shift for Ultrasound Image Segmentation via Fast and Universal Style Transfer
Zhendong Liu, Xin Yang, Rui Gao +9
Deep Neural Networks (DNNs) suffer from the performance degradation when image appearance shift occurs, especially in ultrasound (US) image segmentation. In this paper, we propose…
Agent with Warm Start and Active Termination for Plane Localization in 3D Ultrasound
Haoran Dou, Xin Yang, Jikuan Qian +8
Standard plane localization is crucial for ultrasound (US) diagnosis. In prenatal US, dozens of standard planes are manually acquired with a 2D probe. It is time-consuming and oper…
Joint Segmentation and Landmark Localization of Fetal Femur in Ultrasound Volumes
Xu Wang, Xin Yang, Haoran Dou +3
Volumetric ultrasound has great potentials in promoting prenatal examinations. Automated solutions are highly desired to efficiently and effectively analyze the massive volumes. Se…
Deep Attentive Features for Prostate Segmentation in 3D Transrectal Ultrasound
Yi Wang, Haoran Dou, Xiaowei Hu +7
Automatic prostate segmentation in transrectal ultrasound (TRUS) images is of essential importance for image-guided prostate interventions and treatment planning. However, developi…