316 citations · 2.9k across the 50 of their papers we have counts for
10 papers · 1 filter
Make-A-Volume: Leveraging Latent Diffusion Models for Cross-Modality 3D Brain MRI Synthesis
Lingting Zhu, Zeyue Xue, Zhenchao Jin +4
Cross-modality medical image synthesis is a critical topic and has the potential to facilitate numerous applications in the medical imaging field. Despite recent successes in deep-…
NestedFormer: Nested Modality-Aware Transformer for Brain Tumor Segmentation
Zhaohu Xing, Lequan Yu, Liang Wan +2
Multi-modal MR imaging is routinely used in clinical practice to diagnose and investigate brain tumors by providing rich complementary information. Previous multi-modal MRI segment…
Robust Medical Image Classification from Noisy Labeled Data with Global and Local Representation Guided Co-training
Cheng Xue, Lequan Yu, Pengfei Chen +2
Deep neural networks have achieved remarkable success in a wide variety of natural image and medical image computing tasks. However, these achievements indispensably rely on accura…
Dual-Teacher++: Exploiting Intra-domain and Inter-domain Knowledge with Reliable Transfer for Cardiac Segmentation
Kang Li, Shujun Wang, Lequan Yu +1
Annotation scarcity is a long-standing problem in medical image analysis area. To efficiently leverage limited annotations, abundant unlabeled data are additionally exploited in se…
Towards Cross-modality Medical Image Segmentation with Online Mutual Knowledge Distillation
Kang Li, Lequan Yu, Shujun Wang +1
The success of deep convolutional neural networks is partially attributed to the massive amount of annotated training data. However, in practice, medical data annotations are usual…
Deep Sinogram Completion with Image Prior for Metal Artifact Reduction in CT Images
Lequan Yu, Zhicheng Zhang, Xiaomeng Li +1
Computed tomography (CT) has been widely used for medical diagnosis, assessment, and therapy planning and guidance. In reality, CT images may be affected adversely in the presence…
Multi-Site Infant Brain Segmentation Algorithms: The iSeg-2019 Challenge
Yue Sun, Kun Gao, Zhengwang Wu +30
To better understand early brain growth patterns in health and disorder, it is critical to accurately segment infant brain magnetic resonance (MR) images into white matter (WM), gr…
MS-Net: Multi-Site Network for Improving Prostate Segmentation with Heterogeneous MRI Data
Quande Liu, Qi Dou, Lequan Yu +1
Automated prostate segmentation in MRI is highly demanded for computer-assisted diagnosis. Recently, a variety of deep learning methods have achieved remarkable progress in this ta…
CANet: Cross-disease Attention Network for Joint Diabetic Retinopathy and Diabetic Macular Edema Grading
Xiaomeng Li, Xiaowei Hu, Lequan Yu +3
Diabetic retinopathy (DR) and diabetic macular edema (DME) are the leading causes of permanent blindness in the working-age population. Automatic grading of DR and DME helps ophtha…
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…