67 citations · 140 across the 48 of their papers we have counts for
10 papers · 1 filter
Complex Organ Mask Guided Radiology Report Generation
Tiancheng Gu, Dongnan Liu, Zhiyuan Li +1
The goal of automatic report generation is to generate a clinically accurate and coherent phrase from a single given X-ray image, which could alleviate the workload of traditional…
ODM3D: Alleviating Foreground Sparsity for Semi-Supervised Monocular 3D Object Detection
Weijia Zhang, Dongnan Liu, Chao Ma +1
Monocular 3D object detection (M3OD) is a significant yet inherently challenging task in autonomous driving due to absence of explicit depth cues in a single RGB image. In this pap…
Improving Multiple Sclerosis Lesion Segmentation Across Clinical Sites: A Federated Learning Approach with Noise-Resilient Training
Lei Bai, Dongang Wang, Michael Barnett +13
Accurately measuring the evolution of Multiple Sclerosis (MS) with magnetic resonance imaging (MRI) critically informs understanding of disease progression and helps to direct ther…
Taxonomy Adaptive Cross-Domain Adaptation in Medical Imaging via Optimization Trajectory Distillation
Jianan Fan, Dongnan Liu, Hang Chang +3
The success of automated medical image analysis depends on large-scale and expert-annotated training sets. Unsupervised domain adaptation (UDA) has been raised as a promising appro…
Exploring Annotation-free Image Captioning with Retrieval-augmented Pseudo Sentence Generation
Zhiyuan Li, Dongnan Liu, Heng Wang +2
Recently, training an image captioner without annotated image-sentence pairs has gained traction. Previous methods have faced limitations due to either using mismatched corpora for…
Topology Repairing of Disconnected Pulmonary Airways and Vessels: Baselines and a Dataset
Ziqiao Weng, Jiancheng Yang, Dongnan Liu +1
Accurate segmentation of pulmonary airways and vessels is crucial for the diagnosis and treatment of pulmonary diseases. However, current deep learning approaches suffer from disco…
SynthMix: Mixing up Aligned Synthesis for Medical Cross-Modality Domain Adaptation
Xinwen Zhang, Chaoyi Zhang, Dongnan Liu +2
The adversarial methods showed advanced performance by producing synthetic images to mitigate the domain shift, a common problem due to the hardship of acquiring labelled data in m…
Unsupervised Domain Adaptation for Neuron Membrane Segmentation based on Structural Features
Yuxiang An, Dongnan Liu, Weidong Cai
AI-enhanced segmentation of neuronal boundaries in electron microscopy (EM) images is crucial for automatic and accurate neuroinformatics studies. To enhance the limited generaliza…
Precise Few-shot Fat-free Thigh Muscle Segmentation in T1-weighted MRI
Sheng Chen, Zihao Tang, Dongnan Liu +5
Precise thigh muscle volumes are crucial to monitor the motor functionality of patients with diseases that may result in various degrees of thigh muscle loss. T1-weighted MRI is th…
A Registration- and Uncertainty-based Framework for White Matter Tract Segmentation With Only One Annotated Subject
Hao Xu, Tengfei Xue, Dongnan Liu +5
White matter (WM) tract segmentation based on diffusion magnetic resonance imaging (dMRI) plays an important role in the analysis of human health and brain diseases. However, the a…